A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

## A

a - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  When all c[i] = 0, a[] becomes normal polynomial coefficients, i.e.
a - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Internal weights from Butcher array (without the first empty row).
a - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Internal weights from Butcher array (without the first empty row).
a - Variable in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Guessed amplitude.
a - Variable in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Amplitude a.
a00 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a01 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a02 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a03 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a1 - Variable in class org.apache.commons.math.geometry.RotationOrder
  Axis of the first rotation.
a10 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a11 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a12 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a13 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a2 - Variable in class org.apache.commons.math.geometry.RotationOrder
  Axis of the second rotation.
a20 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a21 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a22 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a23 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a3 - Variable in class org.apache.commons.math.geometry.RotationOrder
  Axis of the third rotation.
a30 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a31 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a32 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
a33 - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
  Coefficients
A70 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Last row of the Butcher-array internal weights, element 0.
A72 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Last row of the Butcher-array internal weights, element 2.
A73 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Last row of the Butcher-array internal weights, element 3.
A74 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Last row of the Butcher-array internal weights, element 4.
A75 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Last row of the Butcher-array internal weights, element 5.
ABS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.abs` method wrapped as a `ComposableFunction`.
abs() - Method in class org.apache.commons.math.complex.Complex
  Return the absolute value of this complex number.
abs() - Method in class org.apache.commons.math.fraction.BigFraction
  Returns the absolute value of this `BigFraction`.
abs() - Method in class org.apache.commons.math.fraction.Fraction
  Returns the absolute value of this fraction.
abscissas - Variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Abscissas for the current method.
ABSCISSAS_2 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Abscissas for the 2 points method.
ABSCISSAS_3 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Abscissas for the 3 points method.
ABSCISSAS_4 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Abscissas for the 4 points method.
ABSCISSAS_5 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Abscissas for the 5 points method.
absoluteAccuracy - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  Maximum absolute error.
absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleRealPointChecker
  Absolute tolerance threshold.
absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Absolute tolerance threshold.
absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Absolute tolerance threshold.
absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Absolute tolerance threshold.
AbstractContinuousDistribution - Class in org.apache.commons.math.distribution
  Base class for continuous distributions.
AbstractContinuousDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Default constructor.
AbstractDistribution - Class in org.apache.commons.math.distribution
  Base class for probability distributions.
AbstractDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractDistribution
  Default constructor.
AbstractEstimator - Class in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
AbstractEstimator() - Constructor for class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Build an abstract estimator for least squares problems.
AbstractFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Basic implementation of `FieldMatrix` methods regardless of the underlying storage.
AbstractFieldMatrix() - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
  Constructor for use with Serializable
AbstractFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
  Creates a matrix with no data
AbstractFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
  Create a new FieldMatrix<T> with the supplied row and column dimensions.
AbstractFormat - Class in org.apache.commons.math.fraction
  Common part shared by both `FractionFormat` and `BigFractionFormat`.
AbstractFormat() - Constructor for class org.apache.commons.math.fraction.AbstractFormat
  Create an improper formatting instance with the default number format for the numerator and denominator.
AbstractFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.AbstractFormat
  Create an improper formatting instance with a custom number format for both the numerator and denominator.
AbstractFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.AbstractFormat
  Create an improper formatting instance with a custom number format for the numerator and a custom number format for the denominator.
AbstractIntegerDistribution - Class in org.apache.commons.math.distribution
  Base class for integer-valued discrete distributions.
AbstractIntegerDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Default constructor.
AbstractIntegrator - Class in org.apache.commons.math.ode
  Base class managing common boilerplate for all integrators.
AbstractIntegrator(String) - Constructor for class org.apache.commons.math.ode.AbstractIntegrator
  Build an instance.
AbstractIntegrator() - Constructor for class org.apache.commons.math.ode.AbstractIntegrator
  Build an instance with a null name.
AbstractIntegrator.EndTimeChecker - Class in org.apache.commons.math.ode
  Specialized event handler to stop integration.
AbstractIntegrator.EndTimeChecker(double) - Constructor for class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
  Build an instance.
AbstractLeastSquaresOptimizer - Class in org.apache.commons.math.optimization.general
  Base class for implementing least squares optimizers.
AbstractLeastSquaresOptimizer() - Constructor for class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Simple constructor with default settings.
AbstractLinearOptimizer - Class in org.apache.commons.math.optimization.linear
  Base class for implementing linear optimizers.
AbstractLinearOptimizer() - Constructor for class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Simple constructor with default settings.
AbstractListChromosome<T> - Class in org.apache.commons.math.genetics
  Chromosome represented by an immutable list of a fixed length.
AbstractListChromosome(List<T>) - Constructor for class org.apache.commons.math.genetics.AbstractListChromosome
  Constructor.
AbstractListChromosome(T[]) - Constructor for class org.apache.commons.math.genetics.AbstractListChromosome
  Constructor.
AbstractMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
  Abstract base class for implementations of MultipleLinearRegression.
AbstractMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
AbstractRandomGenerator - Class in org.apache.commons.math.random
  Abstract class implementing the `RandomGenerator` interface.
AbstractRandomGenerator() - Constructor for class org.apache.commons.math.random.AbstractRandomGenerator
  Construct a RandomGenerator.
AbstractRealMatrix - Class in org.apache.commons.math.linear
  Basic implementation of RealMatrix methods regardless of the underlying storage.
AbstractRealMatrix() - Constructor for class org.apache.commons.math.linear.AbstractRealMatrix
  Creates a matrix with no data
AbstractRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.AbstractRealMatrix
  Create a new RealMatrix with the supplied row and column dimensions.
AbstractRealVector - Class in org.apache.commons.math.linear
  This class provides default basic implementations for many methods in the `RealVector` interface with.
AbstractRealVector() - Constructor for class org.apache.commons.math.linear.AbstractRealVector
AbstractRealVector.EntryImpl - Class in org.apache.commons.math.linear
  An entry in the vector.
AbstractRealVector.EntryImpl() - Constructor for class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
  Simple constructor.
AbstractRealVector.SparseEntryIterator - Class in org.apache.commons.math.linear
  This class should rare be used, but is here to provide a default implementation of sparseIterator(), which is implemented by walking over the entries, skipping those whose values are the default one.
AbstractRealVector.SparseEntryIterator() - Constructor for class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
  Simple constructor.
AbstractScalarDifferentiableOptimizer - Class in org.apache.commons.math.optimization.general
  Base class for implementing optimizers for multivariate scalar functions.
AbstractScalarDifferentiableOptimizer() - Constructor for class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Simple constructor with default settings.
AbstractStepInterpolator - Class in org.apache.commons.math.ode.sampling
  This abstract class represents an interpolator over the last step during an ODE integration.
AbstractStepInterpolator() - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Simple constructor.
AbstractStepInterpolator(double[], boolean) - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Simple constructor.
AbstractStepInterpolator(AbstractStepInterpolator) - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Copy constructor.
AbstractStorelessUnivariateStatistic - Class in org.apache.commons.math.stat.descriptive
  Abstract implementation of the `StorelessUnivariateStatistic` interface.
AbstractStorelessUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
AbstractUnivariateRealOptimizer - Class in org.apache.commons.math.optimization.univariate
  Provide a default implementation for several functions useful to generic optimizers.
AbstractUnivariateRealOptimizer(int, double) - Constructor for class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Construct a solver with given iteration count and accuracy.
AbstractUnivariateStatistic - Class in org.apache.commons.math.stat.descriptive
  Abstract base class for all implementations of the `UnivariateStatistic` interface.
AbstractUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
accuracy - Variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  If the median residual at a certain robustness iteration is less than this amount, no more iterations are done.
ACOS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.abs` method wrapped as a `ComposableFunction`.
acos() - Method in class org.apache.commons.math.complex.Complex
  Compute the inverse cosine of this complex number.
AdamsBashforthIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements explicit Adams-Bashforth integrators for Ordinary Differential Equations.
AdamsBashforthIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
  Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsBashforthIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
  Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsIntegrator - Class in org.apache.commons.math.ode.nonstiff
  Base class for `Adams-Bashforth` and `Adams-Moulton` integrators.
AdamsIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Build an Adams integrator with the given order and step control prameters.
AdamsIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Build an Adams integrator with the given order and step control parameters.
AdamsMoultonIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements implicit Adams-Moulton integrators for Ordinary Differential Equations.
AdamsMoultonIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
  Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
  Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonIntegrator.Corrector - Class in org.apache.commons.math.ode.nonstiff
  Corrector for current state in Adams-Moulton method.
AdamsMoultonIntegrator.Corrector(double[], double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Simple constructor.
AdamsNordsieckTransformer - Class in org.apache.commons.math.ode.nonstiff
  Transformer to Nordsieck vectors for Adams integrators.
AdamsNordsieckTransformer(int) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Simple constructor.
AdaptiveStepsizeIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This abstract class holds the common part of all adaptive stepsize integrators for Ordinary Differential Equations.
AdaptiveStepsizeIntegrator(String, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Build an integrator with the given stepsize bounds.
AdaptiveStepsizeIntegrator(String, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Build an integrator with the given stepsize bounds.
ADD - Static variable in class org.apache.commons.math.analysis.BinaryFunction
  The + operator method wrapped as a `BinaryFunction`.
add(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function adding the instance and another function.
add(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function adding a constant term to the instance.
add(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Add a polynomial to the instance.
add(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the sum of this complex number and the given complex number.
add(T) - Method in interface org.apache.commons.math.FieldElement
  Compute this + a.
add(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
  Adds the value of this fraction to the passed `BigInteger`, returning the result in reduced form.
add(int) - Method in class org.apache.commons.math.fraction.BigFraction
  Adds the value of this fraction to the passed `integer`, returning the result in reduced form.
add(long) - Method in class org.apache.commons.math.fraction.BigFraction
  Adds the value of this fraction to the passed `long`, returning the result in reduced form.
add(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
  Adds the value of this fraction to another, returning the result in reduced form.
add(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
  Adds the value of this fraction to another, returning the result in reduced form.
add(int) - Method in class org.apache.commons.math.fraction.Fraction
  Add an integer to the fraction.
add(Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
  Add a vector to the instance.
add(double, Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
  Add a scaled vector to the instance.
add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Compute the sum of this and m.
add(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Compute the sum of this and m.
add(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute the sum of this and v.
add(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute the sum of this and v.
add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Compute the sum of this and m.
add(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Compute the sum of this and `m`.
add(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Compute the sum of this and m.
add(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Compute the sum of this and `m`.
add(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the sum of this and v.
add(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the sum of this and v.
add(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the sum of this and v.
add(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the sum of this and v.
add(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the sum of this and v.
add(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the sum of this and v.
add(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Compute the sum of this and m.
add(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Compute the sum of this and `m`.
add(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Compute the sum of this and `m`.
add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Compute the sum of this and m.
add(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Compute the sum of this and `m`.
add(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Compute the sum of this and m.
add(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Compute the sum of this and `m`.
add(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Compute the sum of this and m.
add(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute the sum of this and v.
add(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute the sum of this and v.
add(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Compute the sum of this and m.
add(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Compute the sum of this and `m`.
add(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute the sum of this and v.
add(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to add two OpenMapRealVectors.
add(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Compute the sum of this and m.
add(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Compute the sum of this and m.
add(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Compute the sum of this and `m`.
add(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Compute the sum of this and v.
add(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Compute the sum of this and v.
add(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Optimized method to add sparse vectors.
add(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute the sum of this and v.
add(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute the sum of this and v.
add(BigReal) - Method in class org.apache.commons.math.util.BigReal
  Compute this + a.
addAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Add two integers, checking for overflow.
addAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
  Add two long integers, checking for overflow.
addAndCheck(long, long, String) - Static method in class org.apache.commons.math.util.MathUtils
  Add two long integers, checking for overflow.
addChromosome(Chromosome) - Method in class org.apache.commons.math.genetics.ListPopulation
  Add the given chromosome to the population.
addChromosome(Chromosome) - Method in interface org.apache.commons.math.genetics.Population
  Add the given chromosome to the population.
addData(double, double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Adds the observation (x,y) to the regression data set.
addData(double[][]) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Adds the observations represented by the elements in `data`.
addElement(double) - Method in interface org.apache.commons.math.util.DoubleArray
  Adds an element to the end of this expandable array
addElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Adds an element to the end of this expandable array.
addElementRolling(double) - Method in interface org.apache.commons.math.util.DoubleArray
  Adds an element to the end of the array and removes the first element in the array.
addElementRolling(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Adds an element to the end of the array and removes the first element in the array.
addEndTimeChecker(double, double, CombinedEventsManager) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Add an event handler for end time checking.
addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Add an events handler.
addEventHandler(EventHandlerWithJacobians, double, double, int) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int) - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Add an event handler to the integrator.
ADDITIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
  additive expansion mode
addMeasurement(WeightedMeasurement) - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Add a new measurement to the set.
addObservedPoint(double, double) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
  Add an observed (x,y) point to the sample with unit weight.
addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
  Add an observed weighted (x,y) point to the sample.
addObservedPoint(WeightedObservedPoint) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
  Add an observed weighted (x,y) point to the sample.
addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter
  Add an observed weighted (x,y) point to the sample.
addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter
  Add an observed weighted (x,y) point to the sample.
addParameter(EstimatedParameter) - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Add a parameter to the problem.
addPoint(T) - Method in class org.apache.commons.math.stat.clustering.Cluster
  Add a point to this cluster.
addStepHandler(StepHandler) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Add a step handler to this integrator.
addStepHandler(StepHandlerWithJacobians) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Add a step handler to this integrator.
addSub(Fraction, boolean) - Method in class org.apache.commons.math.fraction.Fraction
  Implement add and subtract using algorithm described in Knuth 4.5.1.
addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Change an entry in the specified row and column.
addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Change an entry in the specified row and column.
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
  Add a value to the data
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Adds the value to the dataset.
addValue(double[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Add an n-tuple to the data
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Add a value to the data
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Adds the value to the dataset.
addValue(double[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Add an n-tuple to the data
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Add a value to the data
addValue(Object) - Method in class org.apache.commons.math.stat.Frequency
  Deprecated. use `Frequency.addValue(Comparable)` instead
addValue(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(int) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(Integer) - Method in class org.apache.commons.math.stat.Frequency
  Deprecated. to be removed in math 3.0
addValue(long) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(char) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
advance(AbstractRealVector.EntryImpl) - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
  Advance an entry up to the next non null one.
advance() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Advance iterator one step further.
advance() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Advance iterator one step further.
after - Variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Current state after correction.
aggregate(Collection<SummaryStatistics>) - Static method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Computes aggregate summary statistics.
aggregateStatistics - Variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
  An additional SummaryStatistics into which values added to these statistics (and possibly others) are aggregated
AggregateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
  An aggregator for `SummaryStatistics` from several data sets or data set partitions.
AggregateSummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Initializes a new AggregateSummaryStatistics with default statistics implementations.
AggregateSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Initializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.
AggregateSummaryStatistics(SummaryStatistics, SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Initializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.
AggregateSummaryStatistics.AggregatingSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
  A SummaryStatistics that also forwards all values added to it to a second `SummaryStatistics` for aggregation.
AggregateSummaryStatistics.AggregatingSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
  Initializes a new AggregatingSummaryStatistics with the specified aggregate statistics object
AINV - Static variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
  Matrix to compute the spline coefficients from the function values and function derivatives values
alpha - Variable in class org.apache.commons.math.distribution.BetaDistributionImpl
  First shape parameter.
alpha - Variable in class org.apache.commons.math.distribution.GammaDistributionImpl
  The shape parameter.
angle(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the angular separation between two vectors.
anovaFValue(Collection<double[]>) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
  Computes the ANOVA F-value for a collection of `double[]` arrays.
anovaFValue(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
  Computes the ANOVA F-value for a collection of `double[]` arrays.
anovaPValue(Collection<double[]>) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
  Computes the ANOVA P-value for a collection of `double[]` arrays.
anovaPValue(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
  Computes the ANOVA P-value for a collection of `double[]` arrays.
anovaStats(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
  This method actually does the calculations (except P-value).
anovaTest(Collection<double[]>, double) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
  Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
anovaTest(Collection<double[]>, double) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
  Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
AnyMatrix - Interface in org.apache.commons.math.linear
  Interface defining very basic matrix operations.
append(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending a vector to this vector.
append(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending a vector to this vector.
append(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending a T to this vector.
append(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending a T array to this vector.
append(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending a vector to this vector.
append(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending a vector to this vector.
append(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending a double to this vector.
append(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending a double array to this vector.
append(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Construct a vector by appending a vector to this vector.
append(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Construct a vector by appending a T to this vector.
append(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Construct a vector by appending a T array to this vector.
append(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to append a OpenMapRealVector.
append(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Construct a vector by appending a vector to this vector.
append(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Construct a vector by appending a double to this vector.
append(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Construct a vector by appending a double array to this vector.
append(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Construct a vector by appending a vector to this vector.
append(double) - Method in interface org.apache.commons.math.linear.RealVector
  Construct a vector by appending a double to this vector.
append(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Construct a vector by appending a double array to this vector.
append(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Construct a vector by appending a vector to this vector.
append(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Construct a vector by appending a T to this vector.
append(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Construct a vector by appending a T array to this vector.
append(ContinuousOutputModel) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Append another model at the end of the instance.
append(StringBuffer, double[], String, String, String) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Append a text representation of an array to a buffer.
apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Apply the given statistic to the data associated with this set of statistics.
apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Apply the given statistic to the data associated with this set of statistics.
applyInverseTo(Vector3D) - Method in class org.apache.commons.math.geometry.Rotation
  Apply the inverse of the rotation to a vector.
applyInverseTo(Rotation) - Method in class org.apache.commons.math.geometry.Rotation
  Apply the inverse of the instance to another rotation.
applyTo(Vector3D) - Method in class org.apache.commons.math.geometry.Rotation
  Apply the rotation to a vector.
applyTo(Rotation) - Method in class org.apache.commons.math.geometry.Rotation
  Apply the instance to another rotation.
argument - Variable in exception org.apache.commons.math.FunctionEvaluationException
  Argument causing function evaluation failure
ArgumentOutsideDomainException - Exception in org.apache.commons.math
  Error thrown when a method is called with an out of bounds argument.
ArgumentOutsideDomainException(double, double, double) - Constructor for exception org.apache.commons.math.ArgumentOutsideDomainException
  Constructs an exception with specified formatted detail message.
arguments - Variable in exception org.apache.commons.math.MathException
  Arguments used to build the message.
arguments - Variable in exception org.apache.commons.math.MathRuntimeException
  Arguments used to build the message.
arity - Variable in class org.apache.commons.math.genetics.TournamentSelection
  number of chromosomes included in the tournament selections
Array2DRowFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Implementation of FieldMatrix<T> using a `FieldElement`[][] array to store entries.
Array2DRowFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Creates a matrix with no data
Array2DRowFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Create a new FieldMatrix<T> with the supplied row and column dimensions.
Array2DRowFieldMatrix(T[][]) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(T[][], boolean) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(T[]) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Create a new (column) FieldMatrix<T> using `v` as the data for the unique column of the `v.length x 1` matrix created.
Array2DRowRealMatrix - Class in org.apache.commons.math.linear
  Implementation of RealMatrix using a double[][] array to store entries and LU decomposition to support linear system solution and inverse.
Array2DRowRealMatrix() - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
  Creates a matrix with no data
Array2DRowRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
  Create a new RealMatrix with the supplied row and column dimensions.
Array2DRowRealMatrix(double[][]) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
  Create a new RealMatrix using the input array as the underlying data array.
Array2DRowRealMatrix(double[][], boolean) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
  Create a new RealMatrix using the input array as the underlying data array.
Array2DRowRealMatrix(double[]) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
  Create a new (column) RealMatrix using `v` as the data for the unique column of the `v.length x 1` matrix created.
ArrayFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  This class implements the `FieldVector` interface with a `FieldElement` array.
ArrayFieldVector(Field<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Build a 0-length vector.
ArrayFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a (size)-length vector of zeros.
ArrayFieldVector(int, T) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct an (size)-length vector with preset values.
ArrayFieldVector(T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector from an array, copying the input array.
ArrayFieldVector(T[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Create a new ArrayFieldVector using the input array as the underlying data array.
ArrayFieldVector(T[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector from part of a array.
ArrayFieldVector(FieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector from another vector, using a deep copy.
ArrayFieldVector(ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector from another vector, using a deep copy.
ArrayFieldVector(ArrayFieldVector<T>, boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector from another vector.
ArrayFieldVector(ArrayFieldVector<T>, ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending one vector to another vector.
ArrayFieldVector(ArrayFieldVector<T>, T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending one vector to another vector.
ArrayFieldVector(T[], ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending one vector to another vector.
ArrayFieldVector(T[], T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
  Construct a vector by appending one vector to another vector.
ArrayRealVector - Class in org.apache.commons.math.linear
  This class implements the `RealVector` interface with a double array.
ArrayRealVector() - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Build a 0-length vector.
ArrayRealVector(int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a (size)-length vector of zeros.
ArrayRealVector(int, double) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct an (size)-length vector with preset values.
ArrayRealVector(double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from an array, copying the input array.
ArrayRealVector(double[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Create a new ArrayRealVector using the input array as the underlying data array.
ArrayRealVector(double[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from part of a array.
ArrayRealVector(Double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from an array.
ArrayRealVector(Double[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from part of a Double array
ArrayRealVector(RealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from another vector, using a deep copy.
ArrayRealVector(ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from another vector, using a deep copy.
ArrayRealVector(ArrayRealVector, boolean) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector from another vector.
ArrayRealVector(ArrayRealVector, ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending one vector to another vector.
ArrayRealVector(ArrayRealVector, RealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending one vector to another vector.
ArrayRealVector(RealVector, ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending one vector to another vector.
ArrayRealVector(ArrayRealVector, double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending one vector to another vector.
ArrayRealVector(double[], ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending one vector to another vector.
ArrayRealVector(double[], double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
  Construct a vector by appending one vector to another vector.
asCollector(BivariateRealFunction, double) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Generates a function that iteratively apply instance function on all elements of an array.
asCollector(BivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Generates a function that iteratively apply instance function on all elements of an array.
asCollector(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Generates a function that iteratively apply instance function on all elements of an array.
asCollector() - Method in class org.apache.commons.math.analysis.ComposableFunction
  Generates a function that iteratively apply instance function on all elements of an array.
ASIN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.asin` method wrapped as a `ComposableFunction`.
asin() - Method in class org.apache.commons.math.complex.Complex
  Compute the inverse sine of this complex number.
assignPointsToClusters(Collection<Cluster<T>>, Collection<T>) - Static method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
  Adds the given points to the closest `Cluster`.
AT_LEAST_ONE_COLUMN_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Message for at least one column.
AT_LEAST_ONE_COLUMN_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Message for at least one column.
AT_LEAST_ONE_ROW_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Message for at least one row.
AT_LEAST_ONE_ROW_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Message for at least one row.
ATAN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.atan` method wrapped as a `ComposableFunction`.
atan() - Method in class org.apache.commons.math.complex.Complex
  Compute the inverse tangent of this complex number.
ATAN2 - Static variable in class org.apache.commons.math.analysis.BinaryFunction
  The `Math.atan2` method wrapped as a `BinaryFunction`.

## B

b - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  External weights for the high order method from Butcher array.
b - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  External weights for the high order method from Butcher array.
B_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 1.
B_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 6.
B_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 7.
B_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 8.
B_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 9.
B_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 10.
B_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 11.
B_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Propagation weights, element 12.
bandwidth - Variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  The bandwidth parameter: when computing the loess fit at a particular point, this fraction of source points closest to the current point is taken into account for computing a least-squares regression.
baseSeqPermutation - Variable in class org.apache.commons.math.genetics.RandomKey
  Base sequence [0,1,...,n-1], permuted accorting to the representation (unmodifiable).
baseSequence(int) - Static method in class org.apache.commons.math.genetics.RandomKey
  Helper for constructor.
before - Variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Current state before correction.
beta - Variable in class org.apache.commons.math.distribution.BetaDistributionImpl
  Second shape parameter.
beta - Variable in class org.apache.commons.math.distribution.GammaDistributionImpl
  The scale parameter.
beta - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Coefficients of the Householder transforms vectors.
beta - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Coefficients of the Householder transforms vectors.
Beta - Class in org.apache.commons.math.special
  This is a utility class that provides computation methods related to the Beta family of functions.
Beta() - Constructor for class org.apache.commons.math.special.Beta
  Default constructor.
BetaDistribution - Interface in org.apache.commons.math.distribution
  Computes the cumulative, inverse cumulative and density functions for the beta distribuiton.
BetaDistributionImpl - Class in org.apache.commons.math.distribution
  Implements the Beta distribution.
BetaDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.BetaDistributionImpl
  Build a new instance.
BetaDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.BetaDistributionImpl
  Build a new instance.
biasCorrected - Variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Determines whether or not bias correction is applied when computing the value of the statisic.
BicubicSplineFunction - Class in org.apache.commons.math.analysis.interpolation
  2D-spline function.
BicubicSplineFunction(double[]) - Constructor for class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
BicubicSplineInterpolatingFunction - Class in org.apache.commons.math.analysis.interpolation
  Function that implements the bicubic spline interpolation.
BicubicSplineInterpolatingFunction(double[], double[], double[][], double[][], double[][], double[][]) - Constructor for class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
BiDiagonalTransformer - Class in org.apache.commons.math.linear
  Class transforming any matrix to bi-diagonal shape.
BiDiagonalTransformer(RealMatrix) - Constructor for class org.apache.commons.math.linear.BiDiagonalTransformer
  Build the transformation to bi-diagonal shape of a matrix.
bigDecimalValue() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as a `BigDecimal`.
bigDecimalValue(int) - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as a `BigDecimal` following the passed rounding mode.
bigDecimalValue(int, int) - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as a `BigDecimal` following the passed scale and rounding mode.
bigDecimalValue() - Method in class org.apache.commons.math.util.BigReal
  Get the BigDecimal value corresponding to the instance.
BigFraction - Class in org.apache.commons.math.fraction
  Representation of a rational number without any overflow.
BigFraction(BigInteger) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a `BigFraction` equivalent to the passed `BigInteger`, ie "num / 1".
BigFraction(BigInteger, BigInteger) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a `BigFraction` given the numerator and denominator as `BigInteger`.
BigFraction(double) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a fraction given the double value.
BigFraction(double, double, int) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a fraction given the double value and maximum error allowed.
BigFraction(double, double, int, int) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a fraction given the double value and either the maximum error allowed or the maximum number of denominator digits.
BigFraction(double, int) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a fraction given the double value and maximum denominator.
BigFraction(int) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a `BigFraction` equivalent to the passed `int`, ie "num / 1".
BigFraction(int, int) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a `BigFraction` given the numerator and denominator as simple `int`.
BigFraction(long) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a `BigFraction` equivalent to the passed long, ie "num / 1".
BigFraction(long, long) - Constructor for class org.apache.commons.math.fraction.BigFraction
  Create a `BigFraction` given the numerator and denominator as simple `long`.
BigFractionField - Class in org.apache.commons.math.fraction
  Representation of the fractional numbers without any overflow field.
BigFractionField() - Constructor for class org.apache.commons.math.fraction.BigFractionField
  Private constructor for the singleton.
BigFractionField.LazyHolder - Class in org.apache.commons.math.fraction
  Holder for the instance.
BigFractionField.LazyHolder() - Constructor for class org.apache.commons.math.fraction.BigFractionField.LazyHolder
BigFractionFormat - Class in org.apache.commons.math.fraction
  Formats a BigFraction number in proper format or improper format.
BigFractionFormat() - Constructor for class org.apache.commons.math.fraction.BigFractionFormat
  Create an improper formatting instance with the default number format for the numerator and denominator.
BigFractionFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.BigFractionFormat
  Create an improper formatting instance with a custom number format for both the numerator and denominator.
BigFractionFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.BigFractionFormat
  Create an improper formatting instance with a custom number format for the numerator and a custom number format for the denominator.
bigFractionMatrixToRealMatrix(FieldMatrix<BigFraction>) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Convert a `FieldMatrix`/`BigFraction` matrix to a `RealMatrix`.
BigMatrix - Interface in org.apache.commons.math.linear
  Deprecated. as of 2.0, replaced by `FieldMatrix` with a `BigReal` parameter
BigMatrixImpl - Class in org.apache.commons.math.linear
  Deprecated. as of 2.0, replaced by `Array2DRowFieldMatrix` with a `BigReal` parameter
BigMatrixImpl() - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Creates a matrix with no data
BigMatrixImpl(int, int) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new BigMatrix with the supplied row and column dimensions.
BigMatrixImpl(BigDecimal[][]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new BigMatrix using `d` as the underlying data array.
BigMatrixImpl(BigDecimal[][], boolean) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new BigMatrix using the input array as the underlying data array.
BigMatrixImpl(double[][]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new BigMatrix using `d` as the underlying data array.
BigMatrixImpl(String[][]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new BigMatrix using the values represented by the strings in `d` as the underlying data array.
BigMatrixImpl(BigDecimal[]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new (column) BigMatrix using `v` as the data for the unique column of the `v.length x 1` matrix created.
BigReal - Class in org.apache.commons.math.util
  Arbitrary precision decimal number.
BigReal(BigDecimal) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a BigDecimal.
BigReal(BigInteger) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a BigInteger.
BigReal(BigInteger, int) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from an unscaled BigInteger.
BigReal(BigInteger, int, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from an unscaled BigInteger.
BigReal(BigInteger, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a BigInteger.
BigReal(char[]) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a characters representation.
BigReal(char[], int, int) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a characters representation.
BigReal(char[], int, int, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a characters representation.
BigReal(char[], MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a characters representation.
BigReal(double) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a double.
BigReal(double, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a double.
BigReal(int) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from an int.
BigReal(int, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from an int.
BigReal(long) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a long.
BigReal(long, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a long.
BigReal(String) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a String representation.
BigReal(String, MathContext) - Constructor for class org.apache.commons.math.util.BigReal
  Build an instance from a String representation.
BigRealField - Class in org.apache.commons.math.util
  Representation of real numbers with arbitrary precision field.
BigRealField() - Constructor for class org.apache.commons.math.util.BigRealField
  Private constructor for the singleton.
BigRealField.LazyHolder - Class in org.apache.commons.math.util
  Holder for the instance.
BigRealField.LazyHolder() - Constructor for class org.apache.commons.math.util.BigRealField.LazyHolder
BinaryChromosome - Class in org.apache.commons.math.genetics
  Chromosome represented by a vector of 0s and 1s.
BinaryChromosome(List<Integer>) - Constructor for class org.apache.commons.math.genetics.BinaryChromosome
  Constructor.
BinaryChromosome(Integer[]) - Constructor for class org.apache.commons.math.genetics.BinaryChromosome
  Constructor.
BinaryFunction - Class in org.apache.commons.math.analysis
  Base class for `BivariateRealFunction` that can be composed with other functions.
BinaryFunction() - Constructor for class org.apache.commons.math.analysis.BinaryFunction
BinaryMutation - Class in org.apache.commons.math.genetics
  Mutation for `BinaryChromosome`s.
BinaryMutation() - Constructor for class org.apache.commons.math.genetics.BinaryMutation
binCount - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  number of bins
binomialCoefficient(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns an exact representation of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
binomialCoefficientDouble(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns a `double` representation of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
binomialCoefficientLog(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the natural `log` of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
BinomialDistribution - Interface in org.apache.commons.math.distribution
  The Binomial Distribution.
BinomialDistributionImpl - Class in org.apache.commons.math.distribution
  The default implementation of `BinomialDistribution`.
BinomialDistributionImpl(int, double) - Constructor for class org.apache.commons.math.distribution.BinomialDistributionImpl
  Create a binomial distribution with the given number of trials and probability of success.
binStats - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  List of SummaryStatistics objects characterizing the bins
BisectionSolver - Class in org.apache.commons.math.analysis.solvers
  Implements the bisection algorithm for finding zeros of univariate real functions.
BisectionSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.BisectionSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `BisectionSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
BisectionSolver() - Constructor for class org.apache.commons.math.analysis.solvers.BisectionSolver
  Construct a solver.
BitsStreamGenerator - Class in org.apache.commons.math.random
  Base class for random number generators that generates bits streams.
BitsStreamGenerator() - Constructor for class org.apache.commons.math.random.BitsStreamGenerator
  Creates a new random number generator.
BivariateRealFunction - Interface in org.apache.commons.math.analysis
  An interface representing a bivariate real function.
BivariateRealGridInterpolator - Interface in org.apache.commons.math.analysis.interpolation
  Interface representing a bivariate real interpolating function where the sample points must be specified on a regular grid.
BLOCK_SIZE - Static variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Block size.
BLOCK_SIZE - Static variable in class org.apache.commons.math.linear.BlockRealMatrix
  Block size.
blockColumns - Variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Number of block columns of the matrix.
blockColumns - Variable in class org.apache.commons.math.linear.BlockRealMatrix
  Number of block columns of the matrix.
BlockFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Cache-friendly implementation of FieldMatrix using a flat arrays to store square blocks of the matrix.
BlockFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.BlockFieldMatrix
  Create a new matrix with the supplied row and column dimensions.
BlockFieldMatrix(T[][]) - Constructor for class org.apache.commons.math.linear.BlockFieldMatrix
  Create a new dense matrix copying entries from raw layout data.
BlockFieldMatrix(int, int, T[][], boolean) - Constructor for class org.apache.commons.math.linear.BlockFieldMatrix
  Create a new dense matrix copying entries from block layout data.
blockHeight(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Get the height of a block.
blockHeight(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Get the height of a block.
BlockRealMatrix - Class in org.apache.commons.math.linear
  Cache-friendly implementation of RealMatrix using a flat arrays to store square blocks of the matrix.
BlockRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.BlockRealMatrix
  Create a new matrix with the supplied row and column dimensions.
BlockRealMatrix(double[][]) - Constructor for class org.apache.commons.math.linear.BlockRealMatrix
  Create a new dense matrix copying entries from raw layout data.
BlockRealMatrix(int, int, double[][], boolean) - Constructor for class org.apache.commons.math.linear.BlockRealMatrix
  Create a new dense matrix copying entries from block layout data.
blockRows - Variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Number of block rows of the matrix.
blockRows - Variable in class org.apache.commons.math.linear.BlockRealMatrix
  Number of block rows of the matrix.
blocks - Variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Blocks of matrix entries.
blocks - Variable in class org.apache.commons.math.linear.BlockRealMatrix
  Blocks of matrix entries.
blockWidth(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Get the width of a block.
blockWidth(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Get the width of a block.
bound - Variable in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Indicator for bound parameters (ie parameters that should not be estimated)
bracket(UnivariateRealFunction, double, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  This method attempts to find two values a and b satisfying `lowerBound <= a < initial < b <= upperBound` `f(a) * f(b) < 0` If f is continuous on `[a,b],` this means that `a` and `b` bracket a root of f.
bracket(UnivariateRealFunction, double, double, double, int) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  This method attempts to find two values a and b satisfying `lowerBound <= a < initial < b <= upperBound` `f(a) * f(b) <= 0` If f is continuous on `[a,b],` this means that `a` and `b` bracket a root of f.
BrentOptimizer - Class in org.apache.commons.math.optimization.univariate
  Implements Richard Brent's algorithm (from his book "Algorithms for Minimization without Derivatives", p.
BrentOptimizer() - Constructor for class org.apache.commons.math.optimization.univariate.BrentOptimizer
  Construct a solver.
BrentSolver - Class in org.apache.commons.math.analysis.solvers
  Implements the Brent algorithm for finding zeros of real univariate functions.
BrentSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.BrentSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `BrentSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
BrentSolver() - Constructor for class org.apache.commons.math.analysis.solvers.BrentSolver
  Construct a solver with default properties.
BrentSolver(double) - Constructor for class org.apache.commons.math.analysis.solvers.BrentSolver
  Construct a solver with the given absolute accuracy.
BrentSolver(int, double) - Constructor for class org.apache.commons.math.analysis.solvers.BrentSolver
  Contstruct a solver with the given maximum iterations and absolute accuracy.
brightestIllumination - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Illumination received from the brightest sample.
brightestSample - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Brightest sample.
brightnessExponent - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
  Exponent used in the power law that computes the weights of the sample data.
brightnessExponent - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Exponent used in the power law that computes the weights of the sample data.
buildArray(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Build an array of elements.
buildArray(Field<T>, int) - Static method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Build an array of elements.
buildArray(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Build an array of elements.
buildArray(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Build an array of elements.
buildArray(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Build an array of elements.
buildMessage(Locale, String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Builds a message string by from a pattern and its arguments.
buildP(int) - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Build the P matrix.
buildPolynomial(int, ArrayList<BigFraction>, PolynomialsUtils.RecurrenceCoefficientsGenerator) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Get the coefficients array for a given degree.
buildSimplex(double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Build an initial simplex.

## C

c - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Centers of the Newton polynomial.
c - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Time steps from Butcher array (without the first zero).
c - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Time steps from Butcher array (without the first zero).
c1 - Variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Update coefficients of the higher order derivatives wrt y'.
C14 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Time step for stage 14 (interpolation only).
C15 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Time step for stage 15 (interpolation only).
C16 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Time step for stage 16 (interpolation only).
C_LIMIT - Static variable in class org.apache.commons.math.special.Gamma
  C limit.
CACHE - Static variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Cache for already computed coefficients.
cachedB - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
  Cached value of B.
cachedD - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Cached value of D.
cachedH - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
  Cached value of H.
cachedL - Variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Cached value of L.
cachedL - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Cached value of L.
cachedL - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Cached value of L.
cachedLT - Variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Cached value of LT.
cachedNormalDeviate - Variable in class org.apache.commons.math.random.AbstractRandomGenerator
  Cached random normal value.
cachedP - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Cached value of P.
cachedP - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Cached value of P.
cachedQ - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
  Cached value of Q.
cachedQ - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
  Cached value of Q.
cachedQT - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
  Cached value of QT.
cachedQt - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
  Cached value of Qt.
cachedR - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
  Cached value of R.
cachedS - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Cached value of S.
cachedT - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
  Cached value of T.
cachedU - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
  Cached value of U.
cachedU - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Cached value of U.
cachedU - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Cached value of U.
cachedU - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Cached value of U.
cachedUt - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Cached value of UT.
cachedV - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
  Cached value of V.
cachedV - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Cached value of V.
cachedV - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Cached value of V.
cachedVt - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Cached value of Vt.
cachedVt - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Cached value of VT.
calculateBeta() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Calculates the beta of multiple linear regression in matrix notation.
calculateBeta() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Calculates beta by GLS.
calculateBeta() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Calculates regression coefficients using OLS.
calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Calculates the beta variance of multiple linear regression in matrix notation.
calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Calculates the variance on the beta by GLS.
calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Calculates the variance on the beta by OLS.
calculateHat() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Compute the "hat" matrix.
calculateResiduals() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Calculates the residuals of multiple linear regression in matrix notation.
calculateYVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Calculates the Y variance of multiple linear regression.
calculateYVariance() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Calculates the variance on the y by GLS.
calculateYVariance() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Calculates the variance on the Y by OLS.
CardanEulerSingularityException - Exception in org.apache.commons.math.geometry
  This class represents exceptions thrown while extractiong Cardan or Euler angles from a rotation.
CardanEulerSingularityException(boolean) - Constructor for exception org.apache.commons.math.geometry.CardanEulerSingularityException
  Simple constructor.
CauchyDistribution - Interface in org.apache.commons.math.distribution
  Cauchy Distribution.
CauchyDistributionImpl - Class in org.apache.commons.math.distribution
  Default implementation of `CauchyDistribution`.
CauchyDistributionImpl() - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
  Creates cauchy distribution with the medain equal to zero and scale equal to one.
CauchyDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
  Create a cauchy distribution using the given median and scale.
CauchyDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
  Create a cauchy distribution using the given median and scale.
CBRT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.cbrt` method wrapped as a `ComposableFunction`.
CEIL - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.ceil` method wrapped as a `ComposableFunction`.
center - Variable in class org.apache.commons.math.stat.clustering.Cluster
  Center of the cluster.
centroidOf(Collection<T>) - Method in interface org.apache.commons.math.stat.clustering.Clusterable
  Returns the centroid of the given Collection of points.
centroidOf(Collection<EuclideanIntegerPoint>) - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
  Returns the centroid of the given Collection of points.
changeIndexSign(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Change the index sign
changeIndexSign(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Change the index sign
CHEBYSHEV_COEFFICIENTS - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Coefficients for Chebyshev polynomials.
checkAdditionCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if a matrix is addition compatible with the instance
checkAdditionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if matrices are addition compatible
checkAllFiniteReal(double[], String) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Check that all elements of an array are finite real numbers.
checkArray(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Checks to make sure that the input long[][] array is rectangular, has at least 2 rows and 2 columns, and has all non-negative entries, throwing IllegalArgumentException if any of these checks fail.
checkBinomial(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Check binomial preconditions.
checkColumnIndex(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if a column index is valid.
checkColumnIndex(AnyMatrix, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if a column index is valid.
checkContractExpand(float, float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Checks the expansion factor and the contraction criteria and throws an IllegalArgumentException if the contractionCriteria is less than the expansionCriteria
checkDimension(int, Object) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Check array dimensions.
checkDimension(int) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Throws DimensionMismatchException if dimension != k.
checkedCumulativeProbability(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Computes the cumulative probablity function and checks for NaN values returned.
checkEmpty() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Throws IllegalStateException if n > 0.
checkEmpty() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Throws IllegalStateException if n > 0.
checkEmpty() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Throws IllegalStateException if n > 0.
checker - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Convergence checker.
checker - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Convergence checker.
checker - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Convergence checker.
checkIndex(int) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Check if an index is valid.
checkIndex(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Check if an index is valid.
checkIndex(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Check if an index is valid.
checkMultiplicationCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if a matrix is multiplication compatible with the instance
checkMultiplicationCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if matrices are multiplication compatible
checkNonNegative(long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Check all entries of the input array are >= 0.
checkNonNegative(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Check all entries of the input array are >= 0.
checkOrder(double[], int, boolean) - Static method in class org.apache.commons.math.util.MathUtils
  Checks that the given array is sorted.
checkPositive(double[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Check all entries of the input array are > 0.
checkRectangular(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Throws IllegalArgumentException if the input array is not rectangular.
checkResultComputed() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Check if a result has been computed.
checkResultComputed() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Check if a result has been computed.
checkRowIndex(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if a row index is valid.
checkRowIndex(AnyMatrix, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if a row index is valid.
checkSampleData(double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Check sample data.
checkSampleData(StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Check sample data.
checkSignificanceLevel(double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Check significance level.
checkStrictlyIncreasing(double[]) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Check that elements of the abscissae array are in a strictly increasing order.
checkSubMatrixIndex(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if submatrix ranges indices are valid.
checkSubMatrixIndex(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if submatrix ranges indices are valid.
checkSubMatrixIndex(AnyMatrix, int, int, int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if submatrix ranges indices are valid.
checkSubMatrixIndex(AnyMatrix, int[], int[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if submatrix ranges indices are valid.
checkSubtractionCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Check if a matrix is subtraction compatible with the instance
checkSubtractionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Check if matrices are subtraction compatible
checkSufficientData(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Throws IllegalArgumentException of the matrix does not have at least two columns and two rows
checkSufficientData(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Throws IllegalArgumentException of the matrix does not have at least two columns and two rows
checkValidity(List<T>) - Method in class org.apache.commons.math.genetics.AbstractListChromosome
  Asserts that `representation` can represent a valid chromosome.
checkValidity(List<Integer>) - Method in class org.apache.commons.math.genetics.BinaryChromosome
  Asserts that `representation` can represent a valid chromosome.
checkValidity(List<Double>) - Method in class org.apache.commons.math.genetics.RandomKey
  Asserts that `representation` can represent a valid chromosome.
checkVectorDimensions(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Check if instance and specified vectors have the same dimension.
checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Check if instance dimension is equal to some expected value.
checkVectorDimensions(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Check if instance and specified vectors have the same dimension.
checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Check if instance dimension is equal to some expected value.
checkVectorDimensions(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Check if instance and specified vectors have the same dimension.
checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Check if instance dimension is equal to some expected value.
chiSquare(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Computes the Chi-Square statistic comparing `observed` and `expected` frequency counts.
chiSquare(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Computes the Chi-Square statistic associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
chiSquare(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Computes the Chi-Square statistic comparing `observed` and `expected` frequency counts.
chiSquare(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquare(double[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquare(long[][]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareDataSetsComparison(long[], long[]) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
  Computes a Chi-Square two sample test statistic comparing bin frequency counts in `observed1` and `observed2`.
ChiSquaredDistribution - Interface in org.apache.commons.math.distribution
  The Chi-Squared Distribution.
ChiSquaredDistributionImpl - Class in org.apache.commons.math.distribution
  The default implementation of `ChiSquaredDistribution`
ChiSquaredDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Create a Chi-Squared distribution with the given degrees of freedom.
ChiSquaredDistributionImpl(double, GammaDistribution) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Deprecated. as of 2.1 (to avoid possibly inconsistent state, the "GammaDistribution" will be instantiated internally)
ChiSquaredDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Create a Chi-Squared distribution with the given degrees of freedom and inverse cumulative probability accuracy.
ChiSquareTest - Interface in org.apache.commons.math.stat.inference
  An interface for Chi-Square tests.
chiSquareTest(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the `observed` frequency counts to those in the `expected` array.
chiSquareTest(double[], long[], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level `alpha`.
chiSquareTest(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
chiSquareTest(long[][], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level `alpha`.
chiSquareTest(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the `observed` frequency counts to those in the `expected` array.
chiSquareTest(double[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level `alpha`.
chiSquareTest(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTest(long[][], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTest - Static variable in class org.apache.commons.math.stat.inference.TestUtils
  Singleton ChiSquareTest instance using default implementation.
chiSquareTest(double[], long[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareTest(double[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareTest(long[][], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareTest(long[][]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareTestDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTestDataSetsComparison(long[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTestDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareTestDataSetsComparison(long[], long[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
chiSquareTestDataSetsComparison(long[], long[]) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
  Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in `observed1` and `observed2`.
chiSquareTestDataSetsComparison(long[], long[], double) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
  Performs a Chi-Square two sample test comparing two binned data sets.
ChiSquareTestImpl - Class in org.apache.commons.math.stat.inference
  Implements Chi-Square test statistics defined in the `UnknownDistributionChiSquareTest` interface.
ChiSquareTestImpl() - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Construct a ChiSquareTestImpl
ChiSquareTestImpl(ChiSquaredDistribution) - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Create a test instance using the given distribution for computing inference statistics.
CholeskyDecomposition - Interface in org.apache.commons.math.linear
  An interface to classes that implement an algorithm to calculate the Cholesky decomposition of a real symmetric positive-definite matrix.
CholeskyDecompositionImpl - Class in org.apache.commons.math.linear
  Calculates the Cholesky decomposition of a matrix.
CholeskyDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Calculates the Cholesky decomposition of the given matrix.
CholeskyDecompositionImpl(RealMatrix, double, double) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Calculates the Cholesky decomposition of the given matrix.
CholeskyDecompositionImpl.Solver - Class in org.apache.commons.math.linear
  Specialized solver.
CholeskyDecompositionImpl.Solver(double[][]) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Build a solver from decomposed matrix.
chooseInitialCenters(Collection<T>, int, Random) - Static method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
  Use K-means++ to choose the initial centers.
Chromosome - Class in org.apache.commons.math.genetics
  Individual in a population.
Chromosome() - Constructor for class org.apache.commons.math.genetics.Chromosome
ChromosomePair - Class in org.apache.commons.math.genetics
  A pair of `Chromosome` objects.
ChromosomePair(Chromosome, Chromosome) - Constructor for class org.apache.commons.math.genetics.ChromosomePair
  Create a chromosome pair.
chromosomes - Variable in class org.apache.commons.math.genetics.ListPopulation
  List of chromosomes
classes() - Method in class org.apache.commons.math.util.TransformerMap
  Returns the Set of Classes used as keys in the map.
ClassicalRungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the classical fourth order Runge-Kutta integrator for Ordinary Differential Equations (it is the most often used Runge-Kutta method).
ClassicalRungeKuttaIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Simple constructor.
ClassicalRungeKuttaStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a step interpolator for the classical fourth order Runge-Kutta integrator.
ClassicalRungeKuttaStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
  Simple constructor.
ClassicalRungeKuttaStepInterpolator(ClassicalRungeKuttaStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
  Copy constructor.
clear() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Clears the cache used by the default implementation of `AbstractRandomGenerator.nextGaussian()`.
clear() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Clears the internal state of the Statistic
clear() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.Frequency
  Clears the frequency table
clear() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Clears all data from the model.
clear() - Method in interface org.apache.commons.math.util.DoubleArray
  Clear the double array
clear() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Clear the array, reset the size to the initialCapacity and the number of elements to zero.
clear() - Method in class org.apache.commons.math.util.TransformerMap
  Clears all the Class to Transformer mappings.
clearEventHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Remove all the event handlers that have been added to the integrator.
clearEventsHandlers() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Remove all the events handlers that have been added to the manager.
clearObservations() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
  Remove all observations.
clearResult() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Convenience function for implementations.
clearResult() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Convenience function for implementations.
clearResult() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Convenience function for implementations.
clearStepHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Remove all the step handlers that have been added to the integrator.
clone() - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
clone(FastFourierTransformer.MultiDimensionalComplexMatrix) - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Copy contents of current array into mdcm.
closeReplayFile() - Method in class org.apache.commons.math.random.ValueServer
  Closes `valuesFileURL` after use in REPLAY_MODE.
Cluster<T extends Clusterable<T>> - Class in org.apache.commons.math.stat.clustering
  Cluster holding a set of `Clusterable` points.
Cluster(T) - Constructor for class org.apache.commons.math.stat.clustering.Cluster
  Build a cluster centered at a specified point.
cluster(Collection<T>, int, int) - Method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
  Runs the K-means++ clustering algorithm.
Clusterable<T> - Interface in org.apache.commons.math.stat.clustering
  Interface for points that can be clustered together.
coeff - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  extrapolation coefficients.
coefficients - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  The coefficients of the polynomial, ordered by degree -- i.e., coefficients[0] is the constant term and coefficients[n] is the coefficient of x^n where n is the degree of the polynomial.
coefficients - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  The coefficients of the polynomial, ordered by degree -- i.e.
coefficients - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  The coefficients of the polynomial, ordered by degree -- i.e.
coefficients - Variable in class org.apache.commons.math.optimization.linear.LinearConstraint
  Coefficients of the constraint (left hand side).
coefficients - Variable in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Coefficients of the constraint (ci).
coefficientsComputed - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Whether the polynomial coefficients are available.
coefficientsComputed - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Whether the polynomial coefficients are available.
cols - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Number of columns of the jacobian matrix.
cols - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Number of columns of the jacobian matrix.
columnLabels - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  The variables each column represents
columns - Variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Number of columns of the matrix.
columns - Variable in class org.apache.commons.math.linear.BlockRealMatrix
  Number of columns of the matrix.
columns - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
  Number of columns of the matrix.
columns - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
  column dimension
combine(UnivariateRealFunction, BivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function combining the instance and another function.
CombinedEventsManager - Class in org.apache.commons.math.ode.events
  This class manages several `event handlers` during integration.
CombinedEventsManager() - Constructor for class org.apache.commons.math.ode.events.CombinedEventsManager
  Simple constructor.
comparatorPermutation(List<S>, Comparator<S>) - Static method in class org.apache.commons.math.genetics.RandomKey
  Generates a representation of a permutation corresponding to the `data` sorted by `comparator`.
compare(Comparable<T>, Comparable<T>) - Method in class org.apache.commons.math.stat.Frequency.NaturalComparator
  Compare the two `Comparable` arguments.
compareTo(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
  Compares this object to another based on size.
compareTo(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
  Compares this object to another based on size.
compareTo(Chromosome) - Method in class org.apache.commons.math.genetics.Chromosome
  Compares two chromosomes based on their fitness.
compareTo(NaturalRanking.IntDoublePair) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
  Compare this IntDoublePair to another pair.
compareTo(BigReal) - Method in class org.apache.commons.math.util.BigReal
compareTo(double, double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Compares two numbers given some amount of allowed error.
Complex - Class in org.apache.commons.math.complex
  Representation of a Complex number - a number which has both a real and imaginary part.
Complex(double, double) - Constructor for class org.apache.commons.math.complex.Complex
  Create a complex number given the real and imaginary parts.
ComplexField - Class in org.apache.commons.math.complex
  Representation of the complex numbers field.
ComplexField() - Constructor for class org.apache.commons.math.complex.ComplexField
  Private constructor for the singleton.
ComplexField.LazyHolder - Class in org.apache.commons.math.complex
  Holder for the instance.
ComplexField.LazyHolder() - Constructor for class org.apache.commons.math.complex.ComplexField.LazyHolder
ComplexFormat - Class in org.apache.commons.math.complex
  Formats a Complex number in cartesian format "Re(c) + Im(c)i".
ComplexFormat() - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with the default imaginary character, 'i', and the default number format for both real and imaginary parts.
ComplexFormat(NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom number format for both real and imaginary parts.
ComplexFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom number format for the real part and a custom number format for the imaginary part.
ComplexFormat(String) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts.
ComplexFormat(String, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.
ComplexFormat(String, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part.
ComplexUtils - Class in org.apache.commons.math.complex
  Static implementations of common `Complex` utilities functions.
ComplexUtils() - Constructor for class org.apache.commons.math.complex.ComplexUtils
  Default constructor.
ComposableFunction - Class in org.apache.commons.math.analysis
  Base class for `UnivariateRealFunction` that can be composed with other functions.
ComposableFunction() - Constructor for class org.apache.commons.math.analysis.ComposableFunction
CompositeFormat - Class in org.apache.commons.math.util
  Base class for formatters of composite objects (complex numbers, vectors ...).
CompositeFormat() - Constructor for class org.apache.commons.math.util.CompositeFormat
computeBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
  Compute bin stats.
computeBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
  Compute bin stats.
computeBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
  Compute bin stats.
computeCapacity(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Compute the capacity needed for a given size.
computeCapacity(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Compute the capacity needed for a given size.
computeCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Calculate the coefficients of Lagrange polynomial from the interpolation data.
computeCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Calculate the normal polynomial coefficients given the Newton form.
computeCoefficients(int, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Compute the interpolation coefficients for dense output.
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Computes the correlation matrix for the columns of the input matrix.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Computes the correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Computes the Spearman's rank correlation matrix for the columns of the input matrix.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.
computeCovarianceMatrix(RealMatrix, boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Compute a covariance matrix from a matrix whose columns represent covariates.
computeCovarianceMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Create a covariance matrix from a matrix whose columns represent covariates.
computeCovarianceMatrix(double[][], boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Compute a covariance matrix from a rectangular array whose columns represent covariates.
computeCovarianceMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Create a covariance matrix from a rectangual array whose columns represent covariates.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Compute the derivatives and check the number of evaluations.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.FirstOrderConverter
  Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[]) - Method in interface org.apache.commons.math.ode.FirstOrderDifferentialEquations
  Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
  Get the current time derivative of the state vector.
computeDistribution() - Method in class org.apache.commons.math.random.ValueServer
  Computes the empirical distribution using values from the file in `valuesFileURL`, using the default number of bins.
computeDistribution(int) - Method in class org.apache.commons.math.random.ValueServer
  Computes the empirical distribution using values from the file in `valuesFileURL` and `binCount` bins.
computeDividedDifference(double[], double[]) - Static method in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
  Returns a copy of the divided difference array.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Compute the state at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Compute the state and derivatives at the interpolated time.
computeJacobians(double, double[], double[], double[][], double[][]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Compute the partial derivatives of ODE with respect to state.
computeJacobians(double, double[], double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.ODEWithJacobians
  Compute the partial derivatives of ODE with respect to state.
computeKey(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Compute the key to access a matrix element
computeKey(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Compute the key to access a matrix element
computeObjectiveGradient(double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Compute the gradient vector.
computeObjectiveValue(double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Compute the objective function value.
computeObjectiveValue(UnivariateRealFunction, double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Compute the objective function value.
computeOmega(int) - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Computes the nth roots of unity.
computeSecondDerivatives(double, double[], double[], double[]) - Method in interface org.apache.commons.math.ode.SecondOrderDifferentialEquations
  Get the current time derivative of the state vector.
computeSplineCoefficients(double[]) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
  Compute the spline coefficients from the list of function values and function partial derivatives values at the four corners of a grid element.
computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
  Compute sample statistics.
computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
  Compute sample statistics.
computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
  Compute sample statistics.
computeStepGrowShrinkFactor(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Compute step grow/shrink factor according to normalized error.
computeUpToDegree(int, int, PolynomialsUtils.RecurrenceCoefficientsGenerator, ArrayList<BigFraction>) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Compute polynomial coefficients up to a given degree.
CONCURRENT_MODIFICATION_MESSAGE - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Message for map modification during iteration.
CONCURRENT_MODIFICATION_MESSAGE - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Message for map modification during iteration.
conjugate() - Method in class org.apache.commons.math.complex.Complex
  Return the conjugate of this complex number.
ConjugateGradientFormula - Enum in org.apache.commons.math.optimization.general
  Available choices of update formulas for the β parameter in `NonLinearConjugateGradientOptimizer`.
ConjugateGradientFormula() - Constructor for enum org.apache.commons.math.optimization.general.ConjugateGradientFormula
CONSTANT_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Always return mu
constantTerm - Variable in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Constant term of the linear equation.
constraints - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Linear constraints.
containsClass(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
  Tests if a Class is present in the TransformerMap.
containsKey(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Check if a value is associated with a key.
containsKey(int, int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Check if the tables contain an element associated with specified key at specified index.
containsKey(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Check if a value is associated with a key.
containsKey(int, int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Check if the tables contain an element associated with specified key at specified index.
containsNaNs(NaturalRanking.IntDoublePair[]) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Checks for presence of NaNs in `ranks.`
containsTransformer(NumberTransformer) - Method in class org.apache.commons.math.util.TransformerMap
  Tests if a NumberTransformer is present in the TransformerMap.
CONTENTS - Static variable in class org.apache.commons.math.MessagesResources_fr
  Non-translated/translated messages arrays.
CONTINUE - Static variable in interface org.apache.commons.math.ode.events.EventHandler
  Continue indicator.
CONTINUE - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Continue indicator.
ContinuedFraction - Class in org.apache.commons.math.util
  Provides a generic means to evaluate continued fractions.
ContinuedFraction() - Constructor for class org.apache.commons.math.util.ContinuedFraction
  Default constructor.
ContinuousDistribution - Interface in org.apache.commons.math.distribution
  Base interface for continuous distributions.
ContinuousOutputModel - Class in org.apache.commons.math.ode
  This class stores all information provided by an ODE integrator during the integration process and build a continuous model of the solution from this.
ContinuousOutputModel() - Constructor for class org.apache.commons.math.ode.ContinuousOutputModel
  Simple constructor.
contract() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Contracts the storage array to the (size of the element set) + 1 - to avoid a zero length array.
contractionCriteria - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The contraction criteria determines when the internal array will be contracted to fit the number of elements contained in the element array + 1.
converged(int, RealPointValuePair, RealPointValuePair) - Method in interface org.apache.commons.math.optimization.RealConvergenceChecker
  Check if the optimization algorithm has converged considering the last points.
converged(int, RealPointValuePair, RealPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleRealPointChecker
  Check if the optimization algorithm has converged considering the last points.
converged(int, RealPointValuePair, RealPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Check if the optimization algorithm has converged considering the last points.
converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Check if the optimization algorithm has converged considering the last points.
converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Check if the optimization algorithm has converged considering the last points.
converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in interface org.apache.commons.math.optimization.VectorialConvergenceChecker
  Check if the optimization algorithm has converged considering the last points.
convergence - Variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Threshold for cost convergence.
convergence - Variable in class org.apache.commons.math.ode.events.EventState
  Convergence threshold for event localization.
ConvergenceException - Exception in org.apache.commons.math
  Error thrown when a numerical computation can not be performed because the numerical result failed to converge to a finite value.
ConvergenceException() - Constructor for exception org.apache.commons.math.ConvergenceException
  Default constructor.
ConvergenceException(String, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
  Constructs an exception with specified formatted detail message.
ConvergenceException(Throwable) - Constructor for exception org.apache.commons.math.ConvergenceException
  Create an exception with a given root cause.
ConvergenceException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
  Constructs an exception with specified formatted detail message and root cause.
ConvergingAlgorithm - Interface in org.apache.commons.math
  Interface for algorithms handling convergence settings.
ConvergingAlgorithmImpl - Class in org.apache.commons.math
  Provide a default implementation for several functions useful to generic converging algorithms.
ConvergingAlgorithmImpl(int, double) - Constructor for class org.apache.commons.math.ConvergingAlgorithmImpl
  Construct an algorithm with given iteration count and accuracy.
copy() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Create a new BigMatrix which is a copy of this.
copy() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math.linear.FieldVector
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math.linear.RealVector
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Copy the instance.
copy() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Copy the instance.
copy() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Copy the instance.
copy() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Copy the instance.
copy() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns a copy of this DescriptiveStatistics instance with the same internal state.
copy(DescriptiveStatistics, DescriptiveStatistics) - Static method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Returns a copy of the statistic with the same internal state.
copy(FirstMoment, FirstMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Returns a copy of the statistic with the same internal state.
copy(FourthMoment, FourthMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Returns a copy of the statistic with the same internal state.
copy(GeometricMean, GeometricMean) - Static method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Returns a copy of the statistic with the same internal state.
copy(Kurtosis, Kurtosis) - Static method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns a copy of the statistic with the same internal state.
copy(Mean, Mean) - Static method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Returns a copy of the statistic with the same internal state.
copy(SecondMoment, SecondMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns a copy of the statistic with the same internal state.
copy(SemiVariance, SemiVariance) - Static method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Returns a copy of the statistic with the same internal state.
copy(Skewness, Skewness) - Static method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns a copy of the statistic with the same internal state.
copy(StandardDeviation, StandardDeviation) - Static method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Returns a copy of the statistic with the same internal state.
copy(ThirdMoment, ThirdMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns a copy of the statistic with the same internal state.
copy(Variance, Variance) - Static method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Returns a copy of the statistic with the same internal state.
copy(Max, Max) - Static method in class org.apache.commons.math.stat.descriptive.rank.Max
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Returns a copy of the statistic with the same internal state.
copy(Min, Min) - Static method in class org.apache.commons.math.stat.descriptive.rank.Min
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns a copy of the statistic with the same internal state.
copy(Percentile, Percentile) - Static method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Copies source to dest.
copy() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns a copy of the statistic with the same internal state.
copy(Product, Product) - Static method in class org.apache.commons.math.stat.descriptive.summary.Product
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  Returns a copy of the statistic with the same internal state.
copy(Sum, Sum) - Static method in class org.apache.commons.math.stat.descriptive.summary.Sum
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Returns a copy of the statistic with the same internal state.
copy(SumOfLogs, SumOfLogs) - Static method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Returns a copy of the statistic with the same internal state.
copy(SumOfSquares, SumOfSquares) - Static method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns a copy of this SummaryStatistics instance with the same internal state.
copy(SummaryStatistics, SummaryStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Returns a copy of this SynchronizedDescriptiveStatistics instance with the same internal state.
copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Copies source to dest.
copy() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns a copy of this SynchronizedSummaryStatistics instance with the same internal state.
copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Copies source to dest.
copy() - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
  Returns a copy of the statistic with the same internal state.
copy(ResizableDoubleArray, ResizableDoubleArray) - Static method in class org.apache.commons.math.util.ResizableDoubleArray
  Copies source to dest, copying the underlying data, so dest is a new, independent copy of source.
copy() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns a copy of the ResizableDoubleArray.
copyArray(double[], double[]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Copy an array.
copyArray(double[][], double[][]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Copy an array.
copyArray(double[], double[]) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
copyBlockPart(T[], int, int, int, int, int, T[], int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Copy a part of a block into another one
copyBlockPart(double[], int, int, int, int, int, double[], int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Copy a part of a block into another one
copyIn(T[][]) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Replaces data with a fresh copy of the input array.
copyIn(double[][]) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Replaces data with a fresh copy of the input array.
copyIn(BigDecimal[][]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Replaces data with a fresh copy of the input array.
copyIn(double[][]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Replaces data with a fresh copy of the input array.
copyIn(String[][]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Replaces data with BigDecimals represented by the strings in the input array.
copyIn(double[][]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Replaces data with a fresh copy of the input array.
copyOut() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns a fresh copy of the underlying data array.
copyOut() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns a fresh copy of the underlying data array.
copyOut() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns a fresh copy of the underlying data array.
copyOut() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns a fresh copy of the underlying data array.
copySubMatrix(int, int, int, int, T[][]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Copy a submatrix.
copySubMatrix(int[], int[], T[][]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Copy a submatrix.
copySubMatrix(int, int, int, int, double[][]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Copy a submatrix.
copySubMatrix(int[], int[], double[][]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Copy a submatrix.
copySubMatrix(int, int, int, int, T[][]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Copy a submatrix.
copySubMatrix(int[], int[], T[][]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Copy a submatrix.
copySubMatrix(int, int, int, int, double[][]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Copy a submatrix.
copySubMatrix(int[], int[], double[][]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Copy a submatrix.
CorrelatedRandomVectorGenerator - Class in org.apache.commons.math.random
  A `RandomVectorGenerator` that generates vectors with with correlated components.
CorrelatedRandomVectorGenerator(double[], RealMatrix, double, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Simple constructor.
CorrelatedRandomVectorGenerator(RealMatrix, double, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Simple constructor.
correlation(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Computes the Pearson's product-moment correlation coefficient between the two arrays.
correlation(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Computes the Spearman's rank correlation coefficient between the two arrays.
correlationMatrix - Variable in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  correlation matrix
COS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.cos` method wrapped as a `ComposableFunction`.
cos() - Method in class org.apache.commons.math.complex.Complex
  Compute the cosine of this complex number.
cosAngle(RealVector, RealVector) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
  Compute the cosine of the angle between 2 vectors.
COSH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.cosh` method wrapped as a `ComposableFunction`.
cosh() - Method in class org.apache.commons.math.complex.Complex
  Compute the hyperbolic cosine of this complex number.
cosh(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the hyperbolic cosine of x.
cost - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Cost value (square root of the sum of the residuals).
cost - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Cost value (square root of the sum of the residuals).
costEvaluations - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Number of cost evaluations.
costPerStep - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  overall cost of applying step reduction up to iteration k+1, in number of calls.
costPerTimeUnit - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  cost per unit step.
costRelativeTolerance - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Desired relative error in the sum of squares.
costRelativeTolerance - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Desired relative error in the sum of squares.
count - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Modifications count.
count - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Modifications count.
Covariance - Class in org.apache.commons.math.stat.correlation
  Computes covariances for pairs of arrays or columns of a matrix.
Covariance() - Constructor for class org.apache.commons.math.stat.correlation.Covariance
  Create a Covariance with no data
Covariance(double[][], boolean) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
  Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(double[][]) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
  Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(RealMatrix, boolean) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
  Create a covariance matrix from a matrix whose columns represent covariates.
Covariance(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
  Create a covariance matrix from a matrix whose columns represent covariates.
covariance(double[], double[], boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Computes the covariance between the two arrays.
covariance(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.Covariance
  Computes the covariance between the two arrays, using the bias-corrected formula.
covarianceImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Covariance statistic implementation - cannot be reset.
covarianceMatrix - Variable in class org.apache.commons.math.stat.correlation.Covariance
  covariance matrix
covarianceToCorrelation(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Derives a correlation matrix from a covariance matrix.
createAdaptor(RandomGenerator) - Static method in class org.apache.commons.math.random.RandomAdaptor
  Factory method to create a `Random` using the supplied `RandomGenerator`.
createArithmeticException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `ArithmeticException` with specified formatted detail message.
createArrayIndexOutOfBoundsException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `ArrayIndexOutOfBoundsException` with specified formatted detail message.
createBigIdentityMatrix(int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0, replaced by `MatrixUtils.createFieldIdentityMatrix(Field, int)`
createBigMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createFieldMatrix(FieldElement[][])`
createBigMatrix(BigDecimal[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createFieldMatrix(FieldElement[][])`
createBigMatrix(BigDecimal[][], boolean) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createFieldMatrix(FieldElement[][])`
createBigMatrix(String[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createFieldMatrix(FieldElement[][])`
createBlocksLayout(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.BlockFieldMatrix
  Create a data array in blocks layout.
createBlocksLayout(int, int) - Static method in class org.apache.commons.math.linear.BlockRealMatrix
  Create a data array in blocks layout.
createChebyshevPolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Create a Chebyshev polynomial of the first kind.
createColumnBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createColumnFieldMatrix(FieldElement[])`
createColumnBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createColumnFieldMatrix(FieldElement[])`
createColumnBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createColumnFieldMatrix(FieldElement[])`
createColumnFieldMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a column `FieldMatrix` using the data from the input array.
createColumnRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a column `RealMatrix` using the data from the input array.
createComplex(double, double) - Method in class org.apache.commons.math.complex.Complex
  Create a complex number given the real and imaginary parts.
createConcurrentModificationException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `ConcurrentModificationException` with specified formatted detail message.
createContributingStatistics() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Creates and returns a `SummaryStatistics` whose data will be aggregated with those of this `AggregateSummaryStatistics`.
createEOFException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `EOFException` with specified formatted detail message.
createFieldDiagonalMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a diagonal matrix with specified elements.
createFieldIdentityMatrix(Field<T>, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns `dimension x dimension` identity matrix.
createFieldMatrix(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `FieldMatrix` with specified dimensions.
createFieldMatrix(T[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `FieldMatrix` whose entries are the the values in the the input array.
createFieldVector(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a `FieldVector` using the data from the input array.
createHermitePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Create a Hermite polynomial.
createIllegalArgumentException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `IllegalArgumentException` with specified formatted detail message.
createIllegalArgumentException(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `IllegalArgumentException` with specified nested `Throwable` root cause.
createIllegalStateException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `IllegalStateException` with specified formatted detail message.
createInternalError(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
  Create an `RuntimeException` for an internal error.
createIOException(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `IOException` with specified nested `Throwable` root cause.
createLaguerrePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Create a Laguerre polynomial.
createLegendrePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Create a Legendre polynomial.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createNoSuchElementException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `NoSuchElementException` with specified formatted detail message.
createNullPointerException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `NullPointerException` with specified formatted detail message.
createParseException(int, String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
  Constructs a new `ParseException` with specified formatted detail message.
createRealDiagonalMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a diagonal matrix with specified elements.
createRealIdentityMatrix(int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns `dimension x dimension` identity matrix.
createRealMatrix(int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `RealMatrix` with specified dimensions.
createRealMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `RealMatrix` whose entries are the the values in the the input array.
createRealVector(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a `RealVector` using the data from the input array.
createRowBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createRowFieldMatrix(FieldElement[])`
createRowBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createRowFieldMatrix(FieldElement[])`
createRowBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deprecated. since 2.0 replaced by `MatrixUtils.createRowFieldMatrix(FieldElement[])`
createRowFieldMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a row `FieldMatrix` using the data from the input array.
createRowRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a row `RealMatrix` using the data from the input array.
createTableau(boolean) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Create the tableau by itself.
crossover(Chromosome, Chromosome) - Method in interface org.apache.commons.math.genetics.CrossoverPolicy
  Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math.genetics.OnePointCrossover
  Performs one point crossover.
crossover(AbstractListChromosome<T>, AbstractListChromosome<T>) - Method in class org.apache.commons.math.genetics.OnePointCrossover
  Helper for `OnePointCrossover.crossover(Chromosome, Chromosome)`.
CrossoverPolicy - Interface in org.apache.commons.math.genetics
  Policy used to create a pair of new chromosomes by performing a crossover operation on a source pair of chromosomes.
crossoverPolicy - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  the crossover policy used by the algorithm.
crossoverRate - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  the rate of crossover for the algorithm.
crossProduct(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the cross-product of two vectors.
cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(int, int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  For this distribution, X, this method returns P(X ≤ x).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  For this distribution, X, this method returns P(X < `x`).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  For this distribution, X, this method returns P(X < x).
cumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.Distribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(double, double) - Method in interface org.apache.commons.math.distribution.Distribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  For this distribution, X, this method returns P(X < x).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  For this distribution, X, this method returns P(X < x).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  For this distribution, X, this method returns P(X < x).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For this distribution, X, this method returns P(X ≤ x).
cumulativeProbability(int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(int, int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  For this distribution, X, this method returns P(X < `x`).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  For this distribution, X, this method returns P(X ≤ x).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  The probability distribution function P(X <= x) for a Poisson distribution.
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  For this distribution, X, this method returns P(X < `x`).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  For this distribution, X, this method returns P(X < `x`).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  The probability distribution function P(X <= x) for a Zipf distribution.
current - Variable in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
  Current entry.
current - Variable in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
  Current entry.
current - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Index of current element.
current - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Index of current element.
currentDegree - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Degree of the interpolation polynoms.
currentDerivative - Variable in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Current derivative.
currentState - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  current state
currentTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  current time
CurveFitter - Class in org.apache.commons.math.optimization.fitting
  Fitter for parametric univariate real functions y = f(x).
CurveFitter(DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.CurveFitter
  Simple constructor.
CurveFitter.TheoreticalValuesFunction - Class in org.apache.commons.math.optimization.fitting
  Vectorial function computing function theoretical values.
CurveFitter.TheoreticalValuesFunction(ParametricRealFunction) - Constructor for class org.apache.commons.math.optimization.fitting.CurveFitter.TheoreticalValuesFunction
  Simple constructor.

## D

D - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Interpolation weights.
d - Variable in class org.apache.commons.math.util.BigReal
  Underlying BigDecimal.
D0 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Shampine (1986) Dense output, element 0.
D2 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Shampine (1986) Dense output, element 2.
D3 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Shampine (1986) Dense output, element 3.
D4 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Shampine (1986) Dense output, element 4.
D5 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Shampine (1986) Dense output, element 5.
D6 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Shampine (1986) Dense output, element 6.
data - Variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Entries of the matrix
data - Variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Entries of the matrix
data - Variable in class org.apache.commons.math.linear.ArrayFieldVector
  Entries of the vector.
data - Variable in class org.apache.commons.math.linear.ArrayRealVector
  Entries of the vector.
data - Variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Entries of the matrix
data - Variable in class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
  Converted array.
data - Variable in class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
  Converted array.
data - Variable in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Entries of the matrix
data - Variable in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Input data
decode(List<T>) - Method in interface org.apache.commons.math.genetics.PermutationChromosome
  Permutes the `sequence` of objects of type T according to the permutation this chromosome represents.
decode(List<T>) - Method in class org.apache.commons.math.genetics.RandomKey
  Permutes the `sequence` of objects of type T according to the permutation this chromosome represents.
decodeGeneric(List<S>, List<Double>, List<Double>) - Static method in class org.apache.commons.math.genetics.RandomKey
  Decodes a permutation represented by `representation` and returns a (generic) list with the permuted values.
decompose(RealMatrix, double) - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Decompose the original square matrix.
DecompositionSolver - Interface in org.apache.commons.math.linear
  Interface handling decomposition algorithms that can solve A × X = B.
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.analysis.solvers.BrentSolver
  Default absolute accuracy
DEFAULT_ABSOLUTE_POSITIVITY_THRESHOLD - Static variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Default threshold below which diagonal elements are considered null and matrix not positive definite.
DEFAULT_ABSOLUTE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleRealPointChecker
  Default absolute threshold.
DEFAULT_ABSOLUTE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Default absolute threshold.
DEFAULT_ABSOLUTE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Default absolute threshold.
DEFAULT_ABSOLUTE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Default absolute threshold.
DEFAULT_ACCURACY - Static variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Default value for accuracy.
DEFAULT_BANDWIDTH - Static variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Default value of the bandwidth parameter.
DEFAULT_BRIGHTNESS_EXPONENT - Static variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Default exponent used the weights calculation.
DEFAULT_CONVERGENCE - Static variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Default threshold for cost convergence.
DEFAULT_EPSILON - Static variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Default convergence criterion.
DEFAULT_EPSILON - Static variable in class org.apache.commons.math.optimization.linear.SimplexSolver
  Default amount of error to accept in floating point comparisons.
DEFAULT_EPSILON - Static variable in class org.apache.commons.math.special.Beta
  Maximum allowed numerical error.
DEFAULT_EPSILON - Static variable in class org.apache.commons.math.special.Gamma
  Maximum allowed numerical error.
DEFAULT_EPSILON - Static variable in class org.apache.commons.math.util.ContinuedFraction
  Maximum allowed numerical error.
DEFAULT_EXPECTED_SIZE - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Default starting size.
DEFAULT_EXPECTED_SIZE - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Default starting size.
DEFAULT_FORMAT - Static variable in class org.apache.commons.math.geometry.Vector3D
  Default format.
DEFAULT_FORMAT - Static variable in class org.apache.commons.math.linear.ArrayRealVector
  Default format.
DEFAULT_IMAGINARY_CHARACTER - Static variable in class org.apache.commons.math.complex.ComplexFormat
  The default imaginary character.
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.BetaDistributionImpl
  Default inverse cumulative probability accurac
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.FDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.GammaDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.TDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_INVERSE_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Default inverse cumulative probability accuracy
DEFAULT_MAX_COST_EVALUATIONS - Static variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Default maximal number of cost evaluations allowed.
DEFAULT_MAX_ITERATIONS - Static variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Default maximum number of iterations for cumulative probability calculations.
DEFAULT_MAX_ITERATIONS - Static variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Default maximal number of iterations allowed.
DEFAULT_MAX_ITERATIONS - Static variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Default maximal number of iterations allowed.
DEFAULT_MAX_ITERATIONS - Static variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Default maximal number of iterations allowed.
DEFAULT_MAXIMUM_ITERATIONS - Static variable in class org.apache.commons.math.analysis.solvers.BrentSolver
  Default maximum number of iterations
DEFAULT_MICROSPHERE_ELEMENTS - Static variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Default number of surface elements that composes the microsphere.
DEFAULT_NAN_STRATEGY - Static variable in class org.apache.commons.math.stat.ranking.NaturalRanking
  default NaN strategy
DEFAULT_PREFIX - Static variable in class org.apache.commons.math.geometry.Vector3DFormat
  The default prefix: "{".
DEFAULT_PREFIX - Static variable in class org.apache.commons.math.linear.RealVectorFormat
  The default prefix: "{".
DEFAULT_RELATIVE_SYMMETRY_THRESHOLD - Static variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Default threshold above which off-diagonal elements are considered too different and matrix not symmetric.
DEFAULT_RELATIVE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleRealPointChecker
  Default relative threshold.
DEFAULT_RELATIVE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Default relative threshold.
DEFAULT_RELATIVE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Default relative threshold.
DEFAULT_RELATIVE_THRESHOLD - Static variable in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Default relative threshold.
DEFAULT_ROBUSTNESS_ITERS - Static variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Default value of the number of robustness iterations.
DEFAULT_SEPARATOR - Static variable in class org.apache.commons.math.geometry.Vector3DFormat
  The default separator: ", ".
DEFAULT_SEPARATOR - Static variable in class org.apache.commons.math.linear.RealVectorFormat
  The default separator: ", ".
DEFAULT_STEADY_STATE_THRESHOLD - Static variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Default threshold for cost steady state detection.
DEFAULT_SUFFIX - Static variable in class org.apache.commons.math.geometry.Vector3DFormat
  The default suffix: "}".
DEFAULT_SUFFIX - Static variable in class org.apache.commons.math.linear.RealVectorFormat
  The default suffix: "}".
DEFAULT_TIES_STRATEGY - Static variable in class org.apache.commons.math.stat.ranking.NaturalRanking
  default ties strategy
DEFAULT_TOO_SMALL - Static variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Default bound to determine effective singularity in LU decomposition
DEFAULT_ZERO_TOLERANCE - Static variable in class org.apache.commons.math.linear.OpenMapRealVector
  Default Tolerance for having a value considered zero.
defaultAbsoluteAccuracy - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  Default maximum absolute error.
DefaultFieldMatrixChangingVisitor<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Default implementation of the `FieldMatrixChangingVisitor` interface.
DefaultFieldMatrixChangingVisitor(T) - Constructor for class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
  Build a new instance.
DefaultFieldMatrixPreservingVisitor<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Default implementation of the `FieldMatrixPreservingVisitor` interface.
DefaultFieldMatrixPreservingVisitor(T) - Constructor for class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
  Build a new instance.
defaultFunctionValueAccuracy - Variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Default maximum error of function.
defaultMaximalIterationCount - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  Default maximum number of iterations.
defaultMinimalIterationCount - Variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  default minimum number of iterations
DefaultRealMatrixChangingVisitor - Class in org.apache.commons.math.linear
  Default implementation of the `RealMatrixChangingVisitor` interface.
DefaultRealMatrixChangingVisitor() - Constructor for class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
DefaultRealMatrixPreservingVisitor - Class in org.apache.commons.math.linear
  Default implementation of the `RealMatrixPreservingVisitor` interface.
DefaultRealMatrixPreservingVisitor() - Constructor for class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
defaultRelativeAccuracy - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  Default maximum relative error.
DefaultTransformer - Class in org.apache.commons.math.util
  A Default NumberTransformer for java.lang.Numbers and Numeric Strings.
DefaultTransformer() - Constructor for class org.apache.commons.math.util.DefaultTransformer
defaultTransformer - Variable in class org.apache.commons.math.util.TransformerMap
  A default Number Transformer for Numbers and numeric Strings.
degree() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Returns the degree of the polynomial
degree() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Returns the degree of the polynomial.
degree() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Returns the degree of the polynomial.
degree - Variable in class org.apache.commons.math.optimization.fitting.PolynomialFitter
  Polynomial degree.
degreesOfFreedom - Variable in class org.apache.commons.math.distribution.TDistributionImpl
  The degrees of freedom
delta - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Grid size
denominator - Variable in class org.apache.commons.math.fraction.BigFraction
  The denominator.
denominator - Variable in class org.apache.commons.math.fraction.Fraction
  The denominator.
denominatorDegreesOfFreedom - Variable in class org.apache.commons.math.distribution.FDistributionImpl
  The numerator degrees of freedom
denominatorFormat - Variable in class org.apache.commons.math.fraction.AbstractFormat
  The format used for the denominator.
denseOutput - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  dense outpute required.
density(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Return the probability density for a particular point.
density(Double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
  Return the probability density for a particular point.
density(Double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Deprecated.
density(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Return the probability density for a particular point.
density(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Returns the probability density for a particular point.
density(Double) - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
  Return the probability density for a particular point.
density(Double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Deprecated.
density(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Return the probability density for a particular point.
density(Double) - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
  Return the probability density for a particular point.
density(Double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Deprecated. - use density(double)
density(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Return the probability density for a particular point.
density(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Returns the probability density for a particular point.
density(Double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Return the probability density for a particular point.
density(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Returns the probability density for a particular point.
density(Double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Deprecated.
density(P) - Method in interface org.apache.commons.math.distribution.HasDensity
  Deprecated. Compute the probability density function.
density(Double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Return the probability density for a particular point.
density(Double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Deprecated.
density(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Returns the probability density for a particular point.
density(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Returns the probability density for a particular point.
density(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Returns the probability density for a particular point.
derivative() - Method in interface org.apache.commons.math.analysis.DifferentiableUnivariateMatrixFunction
  Returns the derivative of the function
derivative() - Method in interface org.apache.commons.math.analysis.DifferentiableUnivariateRealFunction
  Returns the derivative of the function
derivative() - Method in interface org.apache.commons.math.analysis.DifferentiableUnivariateVectorialFunction
  Returns the derivative of the function
derivative() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Returns the derivative as a UnivariateRealFunction
derivative() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Returns the derivative of the polynomial spline function as a UnivariateRealFunction
derivative() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Returns the derivative of the function
DerivativeException - Exception in org.apache.commons.math.ode
  This exception is made available to users to report the error conditions that are triggered while computing the differential equations.
DerivativeException(String, Object...) - Constructor for exception org.apache.commons.math.ode.DerivativeException
  Simple constructor.
DerivativeException(Throwable) - Constructor for exception org.apache.commons.math.ode.DerivativeException
  Build an instance from an underlying cause.
DescriptiveStatistics - Class in org.apache.commons.math.stat.descriptive
  Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data.
DescriptiveStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Construct a DescriptiveStatistics instance with an infinite window
DescriptiveStatistics(int) - Constructor for class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Construct a DescriptiveStatistics instance with the specified window
DescriptiveStatistics(DescriptiveStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Copy constructor.
deserializeRealMatrix(Object, String, ObjectInputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deserialize a `RealMatrix` field in a class.
deserializeRealVector(Object, String, ObjectInputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Deserialize a `RealVector` field in a class.
determineLMDirection(double[], double[], double[], double[]) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Solve a*x = b and d*x = 0 in the least squares sense.
determineLMDirection(double[], double[], double[], double[]) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Solve a*x = b and d*x = 0 in the least squares sense.
determineLMParameter(double[], double, double[], double[], double[], double[]) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Determine the Levenberg-Marquardt parameter.
determineLMParameter(double[], double, double[], double[], double[], double[]) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Determine the Levenberg-Marquardt parameter.
dev - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Deviation of most recently added value from previous first moment.
df(double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes approximate degrees of freedom for 2-sample t-test.
dfbg - Variable in class org.apache.commons.math.stat.inference.OneWayAnovaImpl.AnovaStats
  Degrees of freedom in numerator (between groups).
dFdP - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Derivatives of yDot with respect to parameters.
dFdY - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Derivatives of yDot with respect to state.
dfwg - Variable in class org.apache.commons.math.stat.inference.OneWayAnovaImpl.AnovaStats
  Degrees of freedom in denominator (within groups).
diagR - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Diagonal elements of the R matrix in the Q.R.
diagR - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Diagonal elements of the R matrix in the Q.R.
DIFFERENT_ROWS_LENGTHS_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Message for different rows lengths.
DIFFERENT_ROWS_LENGTHS_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Message for different rows lengths.
DifferentiableMultivariateRealFunction - Interface in org.apache.commons.math.analysis
  Extension of `MultivariateRealFunction` representing a differentiable multivariate real function.
DifferentiableMultivariateRealOptimizer - Interface in org.apache.commons.math.optimization
  This interface represents an optimization algorithm for `scalar differentiable objective functions`.
DifferentiableMultivariateVectorialFunction - Interface in org.apache.commons.math.analysis
  Extension of `MultivariateVectorialFunction` representing a differentiable multivariate vectorial function.
DifferentiableMultivariateVectorialOptimizer - Interface in org.apache.commons.math.optimization
  This interface represents an optimization algorithm for `vectorial differentiable objective functions`.
DifferentiableUnivariateMatrixFunction - Interface in org.apache.commons.math.analysis
  Extension of `UnivariateMatrixFunction` representing a differentiable univariate matrix function.
DifferentiableUnivariateRealFunction - Interface in org.apache.commons.math.analysis
  Extension of `UnivariateRealFunction` representing a differentiable univariate real function.
DifferentiableUnivariateVectorialFunction - Interface in org.apache.commons.math.analysis
  Extension of `UnivariateVectorialFunction` representing a differentiable univariate vectorial function.
differentiate(double[]) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Returns the coefficients of the derivative of the polynomial with the given coefficients.
digamma(double) - Static method in class org.apache.commons.math.special.Gamma
  Computes the digamma function of x.
DIGEST_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Use empirical distribution.
dim - Variable in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
  Dimension of the vector.
dimension - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
  Space dimension.
dimension - Variable in class org.apache.commons.math.ode.FirstOrderConverter
  second order problem dimension.
dimension - Variable in class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
  Dimension of the problem.
dimension - Variable in class org.apache.commons.math.random.UnitSphereRandomVectorGenerator
  Space dimension.
dimension1 - Variable in exception org.apache.commons.math.DimensionMismatchException
  First dimension.
dimension2 - Variable in exception org.apache.commons.math.DimensionMismatchException
  Second dimension.
DIMENSION_MISMATCH_MESSAGE - Static variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Message for dimension mismatch.
DIMENSION_MISMATCH_MESSAGE - Static variable in class org.apache.commons.math.transform.FastFourierTransformer
  Message for dimension mismatch.
DimensionMismatchException - Exception in org.apache.commons.math
  Error thrown when two dimensions differ.
DimensionMismatchException(int, int) - Constructor for exception org.apache.commons.math.DimensionMismatchException
  Construct an exception from the mismatched dimensions
dimensionSize - Variable in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Size in all dimensions.
direction - Variable in enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
  boolean value UPSIDE <-> true
DirectSearchOptimizer - Class in org.apache.commons.math.optimization.direct
  This class implements simplex-based direct search optimization algorithms.
DirectSearchOptimizer() - Constructor for class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Simple constructor.
dirtyState - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  indicator for dirty state.
discardExtremeElements(int, boolean) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Discards the `i`first or last elements of the array, depending on the value of `front`.``
discardFrontElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Discards the `i`initial elements of the array.``
discardMostRecentElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Discards the `i`last elements of the array.``
DiscreteDistribution - Interface in org.apache.commons.math.distribution
  Base interface for discrete distributions.
dispatchCompoundState(double[], double[], double[][], double[][]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Dispatch a compound state array into state and jacobians arrays.
distance(Rotation, Rotation) - Static method in class org.apache.commons.math.geometry.Rotation
  Compute the distance between two rotations.
distance(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the distance between two vectors according to the L2 norm.
distance(double[], double[]) - Static method in class org.apache.commons.math.util.MathUtils
  Calculates the L2 (Euclidean) distance between two points.
distance(int[], int[]) - Static method in class org.apache.commons.math.util.MathUtils
  Calculates the L2 (Euclidean) distance between two points.
distance1(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the distance between two vectors according to the L1 norm.
distance1(double[], double[]) - Static method in class org.apache.commons.math.util.MathUtils
  Calculates the L1 (sum of abs) distance between two points.
distance1(int[], int[]) - Static method in class org.apache.commons.math.util.MathUtils
  Calculates the L1 (sum of abs) distance between two points.
distanceFrom(T) - Method in interface org.apache.commons.math.stat.clustering.Clusterable
  Returns the distance from the given point.
distanceFrom(EuclideanIntegerPoint) - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
  Returns the distance from the given point.
distanceInf(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the distance between two vectors according to the L∞ norm.
distanceInf(double[], double[]) - Static method in class org.apache.commons.math.util.MathUtils
  Calculates the L∞ (max of abs) distance between two points.
distanceInf(int[], int[]) - Static method in class org.apache.commons.math.util.MathUtils
  Calculates the L∞ (max of abs) distance between two points.
distanceSq(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the square of the distance between two vectors.
Distribution - Interface in org.apache.commons.math.distribution
  Base interface for probability distributions.
distribution - Variable in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Distribution used to compute inference statistics.
distribution - Variable in class org.apache.commons.math.stat.inference.TTestImpl
  Distribution used to compute inference statistics.
distribution - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  the distribution used to compute inference statistics.
DIVIDE - Static variable in class org.apache.commons.math.analysis.BinaryFunction
  The / operator method wrapped as a `BinaryFunction`.
divide(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function dividing the instance by another function.
divide(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the quotient of this complex number and the given complex number.
divide(T) - Method in interface org.apache.commons.math.FieldElement
  Compute this ÷ a.
divide(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
  Divide the value of this fraction by the passed `BigInteger`, ie "this * 1 / bg", returning the result in reduced form.
divide(int) - Method in class org.apache.commons.math.fraction.BigFraction
  Divide the value of this fraction by the passed `int`, ie "this * 1 / i", returning the result in reduced form.
divide(long) - Method in class org.apache.commons.math.fraction.BigFraction
  Divide the value of this fraction by the passed `long`, ie "this * 1 / l", returning the result in reduced form.
divide(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
  Divide the value of this fraction by another, returning the result in reduced form.
divide(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
  Divide the value of this fraction by another.
divide(int) - Method in class org.apache.commons.math.fraction.Fraction
  Divide the fraction by an integer.
divide(BigReal) - Method in class org.apache.commons.math.util.BigReal
  Compute this ÷ a.
DividedDifferenceInterpolator - Class in org.apache.commons.math.analysis.interpolation
  Implements the Divided Difference Algorithm for interpolation of real univariate functions.
DividedDifferenceInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
divideRow(int, double) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Subtracts a multiple of one row from another.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Really copy the finalized instance.
doFinalize() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Really finalize the step.
doFinalize() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Really finalize the step.
doIteration(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Runs one iteration of the Simplex method on the given model.
doOptimize() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Perform the bulk of optimization algorithm.
doOptimize() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Perform the bulk of optimization algorithm.
doOptimize() - Method in class org.apache.commons.math.optimization.general.GaussNewtonOptimizer
  Perform the bulk of optimization algorithm.
doOptimize() - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Perform the bulk of optimization algorithm.
doOptimize() - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Perform the bulk of optimization algorithm.
doOptimize() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Perform the bulk of optimization algorithm.
doOptimize() - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Perform the bulk of optimization algorithm.
doRemove(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Remove an element at specified index.
doRemove(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Remove an element at specified index.
DormandPrince54Integrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the 5(4) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince54Integrator(double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Simple constructor.
DormandPrince54Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Simple constructor.
DormandPrince54StepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class represents an interpolator over the last step during an ODE integration for the 5(4) Dormand-Prince integrator.
DormandPrince54StepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Simple constructor.
DormandPrince54StepInterpolator(DormandPrince54StepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Copy constructor.
DormandPrince853Integrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the 8(5,3) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince853Integrator(double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Simple constructor.
DormandPrince853Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Simple constructor.
DormandPrince853StepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class represents an interpolator over the last step during an ODE integration for the 8(5,3) Dormand-Prince integrator.
DormandPrince853StepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Simple constructor.
DormandPrince853StepInterpolator(DormandPrince853StepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Copy constructor.
dotProduct(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
  Compute the dot-product of two vectors.
dotProduct(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute the dot product.
dotProduct(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute the dot product.
dotProduct(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the dot product.
dotProduct(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the dot product.
dotProduct(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the dot product.
dotProduct(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the dot product.
dotProduct(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the dot product.
dotProduct(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the dot product.
dotProduct(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute the dot product.
dotProduct(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute the dot product.
dotProduct(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to compute the dot product with an OpenMapRealVector.
dotProduct(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute the dot product.
dotProduct(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Compute the dot product.
dotProduct(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Compute the dot product.
dotProduct(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute the dot product.
dotProduct(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute the dot product.
DoubleArray - Interface in org.apache.commons.math.util
  Provides a standard interface for double arrays.
doubleValue() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as a `double`.
doubleValue() - Method in class org.apache.commons.math.fraction.Fraction
  Gets the fraction as a `double`.
doubleValue() - Method in class org.apache.commons.math.util.BigReal
  Get the double value corresponding to the instance.
DOWNSIDE_VARIANCE - Static variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  The DOWNSIDE Direction is used to specify that the observations below the cutoff point will be used to calculate SemiVariance
dropPhase1Objective() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Removes the phase 1 objective function, positive cost non-artificial variables, and the non-basic artificial variables from this tableau.
DummyStepHandler - Class in org.apache.commons.math.ode.sampling
  This class is a step handler that does nothing.
DummyStepHandler() - Constructor for class org.apache.commons.math.ode.sampling.DummyStepHandler
  Private constructor.
DummyStepHandler.LazyHolder - Class in org.apache.commons.math.ode.sampling
  Holder for the instance.
DummyStepHandler.LazyHolder() - Constructor for class org.apache.commons.math.ode.sampling.DummyStepHandler.LazyHolder
DummyStepInterpolator - Class in org.apache.commons.math.ode.sampling
  This class is a step interpolator that does nothing.
DummyStepInterpolator() - Constructor for class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Simple constructor.
DummyStepInterpolator(double[], double[], boolean) - Constructor for class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Simple constructor.
DummyStepInterpolator(DummyStepInterpolator) - Constructor for class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Copy constructor.
DuplicateSampleAbscissaException - Exception in org.apache.commons.math
  Exception thrown when a sample contains several entries at the same abscissa.
DuplicateSampleAbscissaException(double, int, int) - Constructor for exception org.apache.commons.math.DuplicateSampleAbscissaException
  Construct an exception indicating the duplicate abscissa.
dydp - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Jacobian with respect to parameters dy/dp.
dydp - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Jacobian with respect to parameters dy/dp.
dydpDot - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Time derivative of the jacobian with respect to parameters dy/dp.
dydy0 - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Jacobian with respect to initial state dy/dy0.
dydy0 - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Jacobian with respect to initial state dy/dy0.
dydy0Dot - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Time derivative of the sacobian with respect to initial state dy/dy0.

## E

E1 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Error array, element 1.
E1_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 1.
E1_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 6.
E1_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 7.
E1_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 8.
E1_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 9.
E1_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 10.
E1_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 11.
E1_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  First error weights array, element 12.
E2_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 1.
E2_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 6.
E2_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 7.
E2_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 8.
E2_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 9.
E2_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 10.
E2_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 11.
E2_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Second error weights array, element 12.
E3 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Error array, element 3.
E4 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Error array, element 4.
E5 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Error array, element 5.
E6 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Error array, element 6.
E7 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Error array, element 7.
ebeDivide(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Element-by-element division.
ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Element-by-element division.
ebeDivide(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Element-by-element division.
ebeDivide(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Element-by-element division.
ebeDivide(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Element-by-element division.
ebeDivide(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Element-by-element division.
ebeDivide(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Element-by-element division.
ebeDivide(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Element-by-element division.
ebeDivide(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Element-by-element division.
ebeDivide(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Element-by-element division.
ebeDivide(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Element-by-element division.
ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Element-by-element division.
ebeDivide(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Element-by-element division.
ebeMultiply(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Element-by-element multiplication.
ebeMultiply(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Element-by-element multiplication.
ebeMultiply(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Element-by-element multiplication.
ebeMultiply(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Element-by-element multiplication.
ebeMultiply(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Element-by-element multiplication.
ebeMultiply(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Element-by-element multiplication.
ebeMultiply(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Element-by-element multiplication.
ebeMultiply(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Element-by-element multiplication.
ebeMultiply(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Element-by-element multiplication.
ebeMultiply(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Element-by-element multiplication.
eDA - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Stored data values
EigenDecomposition - Interface in org.apache.commons.math.linear
  An interface to classes that implement an algorithm to calculate the eigen decomposition of a real matrix.
eigenDecomposition - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Eigen decomposition of the tridiagonal matrix.
EigenDecompositionImpl - Class in org.apache.commons.math.linear
  Calculates the eigen decomposition of a real symmetric matrix.
EigenDecompositionImpl(RealMatrix, double) - Constructor for class org.apache.commons.math.linear.EigenDecompositionImpl
  Calculates the eigen decomposition of the given symmetric matrix.
EigenDecompositionImpl(double[], double[], double) - Constructor for class org.apache.commons.math.linear.EigenDecompositionImpl
  Calculates the eigen decomposition of the symmetric tridiagonal matrix.
EigenDecompositionImpl.Solver - Class in org.apache.commons.math.linear
  Specialized solver.
EigenDecompositionImpl.Solver(double[], double[], ArrayRealVector[]) - Constructor for class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Build a solver from decomposed matrix.
eigenvectors - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Eigenvectors.
eigenvectors - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Eigenvectors.
elitismRate - Variable in class org.apache.commons.math.genetics.ElitisticListPopulation
  percentage of chromosomes copied to the next generation
ElitisticListPopulation - Class in org.apache.commons.math.genetics
  Population of chromosomes which uses elitism (certain percentace of the best chromosomes is directly copied to the next generation).
ElitisticListPopulation(List<Chromosome>, int, double) - Constructor for class org.apache.commons.math.genetics.ElitisticListPopulation
  Creates a new ElitisticListPopulation instance.
ElitisticListPopulation(int, double) - Constructor for class org.apache.commons.math.genetics.ElitisticListPopulation
  Creates a new ListPopulation instance and initializes its inner chromosome list.
EmbeddedRungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the common part of all embedded Runge-Kutta integrators for Ordinary Differential Equations.
EmbeddedRungeKuttaIntegrator(String, boolean, double[], double[][], double[], RungeKuttaStepInterpolator, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Build a Runge-Kutta integrator with the given Butcher array.
EmbeddedRungeKuttaIntegrator(String, boolean, double[], double[][], double[], RungeKuttaStepInterpolator, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Build a Runge-Kutta integrator with the given Butcher array.
EmpiricalDistribution - Interface in org.apache.commons.math.random
  Represents an empirical probability distribution -- a probability distribution derived from observed data without making any assumptions about the functional form of the population distribution that the data come from.
empiricalDistribution - Variable in class org.apache.commons.math.random.ValueServer
  Empirical probability distribution for use with DIGEST_MODE.
EmpiricalDistributionImpl - Class in org.apache.commons.math.random
  Implements `EmpiricalDistribution` interface.
EmpiricalDistributionImpl() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl
  Creates a new EmpiricalDistribution with the default bin count.
EmpiricalDistributionImpl(int) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl
  Creates a new EmpiricalDistribution with the specified bin count.
EmpiricalDistributionImpl.ArrayDataAdapter - Class in org.apache.commons.math.random
  `DataAdapter` for data provided as array of doubles.
EmpiricalDistributionImpl.ArrayDataAdapter(double[]) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
  Construct an ArrayDataAdapter from a double[] array
EmpiricalDistributionImpl.DataAdapter - Class in org.apache.commons.math.random
  Provides methods for computing `sampleStats` and `beanStats` abstracting the source of data.
EmpiricalDistributionImpl.DataAdapter() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
EmpiricalDistributionImpl.DataAdapterFactory - Class in org.apache.commons.math.random
  Factory of `DataAdapter` objects.
EmpiricalDistributionImpl.DataAdapterFactory() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapterFactory
EmpiricalDistributionImpl.StreamDataAdapter - Class in org.apache.commons.math.random
  `DataAdapter` for data provided through some input stream
EmpiricalDistributionImpl.StreamDataAdapter(BufferedReader) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
  Create a StreamDataAdapter from a BufferedReader
EMPTY_ARRAY_MESSAGE - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Message for empty coefficients array.
end() - Method in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
  End visiting a matrix.
end() - Method in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
  End visiting a matrix.
end() - Method in class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
  End visiting a matrix.
end() - Method in class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
  End visiting a matrix.
end() - Method in interface org.apache.commons.math.linear.FieldMatrixChangingVisitor
  End visiting a matrix.
end() - Method in interface org.apache.commons.math.linear.FieldMatrixPreservingVisitor
  End visiting a matrix.
end() - Method in interface org.apache.commons.math.linear.RealMatrixChangingVisitor
  End visiting a matrix.
end() - Method in interface org.apache.commons.math.linear.RealMatrixPreservingVisitor
  End visiting a matrix.
end() - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  End visiting te Nordsieck vector.
endTime - Variable in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
  Desired end time.
entries - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
  Storage for (sparse) matrix elements.
entries - Variable in class org.apache.commons.math.linear.OpenMapRealVector
  Entries of the vector.
entries - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
  Storage for (sparse) matrix elements.
entries - Variable in class org.apache.commons.math.linear.SparseFieldVector
  Entries of the vector.
epsilon - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Convergence criterion for cumulative probability.
epsilon - Variable in class org.apache.commons.math.linear.OpenMapRealVector
  Tolerance for having a value considered zero.
epsilon - Variable in class org.apache.commons.math.optimization.linear.SimplexSolver
  Amount of error to accept in floating point comparisons.
epsilon - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Amount of error to accept in floating point comparisons.
EPSILON - Static variable in class org.apache.commons.math.util.MathUtils
  Smallest positive number such that 1 - EPSILON is not numerically equal to 1.
EQUAL_VERTICES_MESSAGE - Static variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Message for equal vertices.
equals(Object) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
equals(Object) - Method in class org.apache.commons.math.complex.Complex
  Test for the equality of two Complex objects.
equals(Object) - Method in class org.apache.commons.math.fraction.BigFraction
  Test for the equality of two fractions.
equals(Object) - Method in class org.apache.commons.math.fraction.Fraction
  Test for the equality of two fractions.
equals(Object) - Method in class org.apache.commons.math.geometry.Vector3D
  Test for the equality of two 3D vectors.
equals(Object) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns true iff `object` is a `FieldMatrix` instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns true iff `object` is a `RealMatrix` instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns true iff `object` is a `BigMatrixImpl` instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Implementation Note: This performs an exact comparison, and as a result it is possible for `a.subtract(b`} to be the zero vector, while `a.equals(b) == false`.
equals(Object) - Method in class org.apache.commons.math.linear.SparseFieldVector
equals(Object) - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
equals(Object) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
equals(Object) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
equals(Object) - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Returns true iff `object` is an `AbstractStorelessUnivariateStatistic` returning the same values as this for `getResult()` and `getN()`
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
  Returns true iff `object` is a `SummaryStatistics` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns true iff `object` is a `SummaryStatistics` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Returns true iff `object` is a `StatisticalSummaryValues` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns true iff `object` is a `SummaryStatistics` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns true iff `object` is a `SummaryStatistics` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns true iff `object` is a `SummaryStatistics` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.Frequency
equals(Object) - Method in class org.apache.commons.math.util.BigReal
equals(Object) - Method in class org.apache.commons.math.util.DefaultTransformer
equals(double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns true iff both arguments are NaN or neither is NaN and they are equal
equals(double, double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns true iff both arguments are equal or within the range of allowed error (inclusive).
equals(double, double, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns true iff both arguments are equal or within the range of allowed error (inclusive).
equals(double[], double[]) - Static method in class org.apache.commons.math.util.MathUtils
  Returns true iff both arguments are null or have same dimensions and all their elements are `equals`
equals(Object) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns true iff object is a ResizableDoubleArray with the same properties as this and an identical internal storage array.
equals(Object) - Method in class org.apache.commons.math.util.TransformerMap
equations - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Differential equations to integrate.
equations - Variable in class org.apache.commons.math.ode.FirstOrderConverter
  Underlying second order equations set.
Erf - Class in org.apache.commons.math.special
  This is a utility class that provides computation methods related to the error functions.
Erf() - Constructor for class org.apache.commons.math.special.Erf
  Default constructor.
erf(double) - Static method in class org.apache.commons.math.special.Erf
  Returns the error function erf(x).
errfac - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Error coefficients for the interpolation.
estimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Solve an estimation problem.
estimate - Variable in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Current value of the parameter
estimate(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
  Deprecated. Solve an estimation problem.
estimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Solve an estimation problem using a least squares criterion.
estimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Solve an estimation problem using the Levenberg-Marquardt algorithm.
EstimatedParameter - Class in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
EstimatedParameter(String, double) - Constructor for class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Simple constructor.
EstimatedParameter(String, double, boolean) - Constructor for class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Simple constructor.
EstimatedParameter(EstimatedParameter) - Constructor for class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Copy constructor.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Compute the error ratio.
estimateError(double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Estimate interpolation error.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Compute the error ratio.
estimateRegressandVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Returns the variance of the regressand, ie Var(y).
estimateRegressandVariance() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
  Returns the variance of the regressand, ie Var(y).
estimateRegressionParameters() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Estimates the regression parameters b.
estimateRegressionParameters() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
  Estimates the regression parameters b.
estimateRegressionParametersStandardErrors() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Returns the standard errors of the regression parameters.
estimateRegressionParametersStandardErrors() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
  Returns the standard errors of the regression parameters.
estimateRegressionParametersVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Estimates the variance of the regression parameters, ie Var(b).
estimateRegressionParametersVariance() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
  Estimates the variance of the regression parameters, ie Var(b).
estimateResiduals() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Estimates the residuals, ie u = y - X*b.
estimateResiduals() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
  Estimates the residuals, ie u = y - X*b.
EstimationException - Exception in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
EstimationException(String, Object...) - Constructor for exception org.apache.commons.math.estimation.EstimationException
  Deprecated. Simple constructor.
EstimationProblem - Interface in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
Estimator - Interface in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
EuclideanIntegerPoint - Class in org.apache.commons.math.stat.clustering
  A simple implementation of `Clusterable` for points with integer coordinates.
EuclideanIntegerPoint(int[]) - Constructor for class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
  Build an instance wrapping an integer array.
EulerIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a simple Euler integrator for Ordinary Differential Equations.
EulerIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Simple constructor.
EulerStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a linear interpolator for step.
EulerStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
  Simple constructor.
EulerStepInterpolator(EulerStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
  Copy constructor.
evaluate(double[], double) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.
evaluate(double[], double[], double) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Evaluate the Lagrange polynomial using Neville's Algorithm.
evaluate(double[], double[], double) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Evaluate the Newton polynomial using nested multiplication.
evaluate(double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Evaluate the objective function on one point.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation calls `AbstractStorelessUnivariateStatistic.clear()`, then invokes `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the the input array, and then uses `AbstractStorelessUnivariateStatistic.getResult()` to compute the return value.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation calls `AbstractStorelessUnivariateStatistic.clear()`, then invokes `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the specified portion of the input array, and then uses `AbstractStorelessUnivariateStatistic.getResult()` to compute the return value.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  Returns the result of evaluating the statistic over the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  Returns the result of evaluating the statistic over the specified entries in the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Returns the geometric mean of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Returns the kurtosis of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns the arithmetic mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns the weighted arithmetic mean of the entries in the input array.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  This method calculates `SemiVariance` for the entire array against the mean, using instance properties varianceDirection and biasCorrection.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns the `SemiVariance` of the designated values against the mean, using instance properties varianceDirection and biasCorrection.
evaluate(double[], SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  This method calculates `SemiVariance` for the entire array against the mean, using the current value of the biasCorrection instance property.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns the `SemiVariance` of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.
evaluate(double[], double, SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns the `SemiVariance` of the designated values against the cutoff in the given direction, using the current value of the biasCorrection instance property.
evaluate(double[], double, SemiVariance.Direction, boolean, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns the `SemiVariance` of the designated values against the cutoff in the given direction with the provided bias correction.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Returns the Skewness of the entries in the specifed portion of the input array.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the input array, or `Double.NaN` if the array is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the input array, or `Double.NaN` if the array is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the weighted variance of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the weighted variance of the entries in the the input array.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the input array, using the precomputed mean value.
evaluate(double[], double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the weighted variance of the entries in the specified portion of the input array, using the precomputed weighted mean value.
evaluate(double[], double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the weighted variance of the values in the input array, using the precomputed weighted mean value.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Returns the maximum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Returns the minimum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns an estimate of the `p`th percentile of the values in the `values` array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns an estimate of the `quantile`th percentile of the designated values in the `values` array.
evaluate(double[], int, int, double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns an estimate of the `p`th percentile of the values in the `values` array, starting with the element in (0-based) position `begin` in the array and including `length` values.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns the product of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns the weighted product of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns the weighted product of the entries in the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  The sum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  The weighted sum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  The weighted sum of the entries in the the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Returns the sum of the natural logs of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Returns the sum of the squares of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[]) - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
  Returns the result of evaluating the statistic over the input array.
evaluate(double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
  Returns the result of evaluating the statistic over the specified entries in the input array.
evaluate(double[], double[]) - Method in interface org.apache.commons.math.stat.descriptive.WeightedEvaluation
  Returns the result of evaluating the statistic over the input array, using the supplied weights.
evaluate(double[], double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.WeightedEvaluation
  Returns the result of evaluating the statistic over the specified entries in the input array, using corresponding entries in the supplied weights array.
evaluate(double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluate(double, double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluate(double, int) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluate(double, double, int) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluateNewSimplex(RealPointValuePair[], double, Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.MultiDirectional
  Compute and evaluate a new simplex.
evaluateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Evaluate all the non-evaluated points of the simplex.
evaluateStep(StepInterpolator) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Evaluate the impact of the proposed step on all managed event handlers.
evaluateStep(StepInterpolator) - Method in class org.apache.commons.math.ode.events.EventState
  Evaluate the impact of the proposed step on the event handler.
evaluations - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Number of evaluations already performed.
evaluations - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Number of evaluations already performed.
evaluations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Number of evaluations already performed.
evaluations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Number of evaluations already performed.
evaluations - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Number of evaluations already performed.
even - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Parity of the permutation associated with the LU decomposition
even - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Parity of the permutation associated with the LU decomposition
EventException - Exception in org.apache.commons.math.ode.events
  This exception is made available to users to report the error conditions that are triggered by `EventHandler`
EventException(String, Object...) - Constructor for exception org.apache.commons.math.ode.events.EventException
  Simple constructor.
EventException(Throwable) - Constructor for exception org.apache.commons.math.ode.events.EventException
  Create an exception with a given root cause.
EventHandler - Interface in org.apache.commons.math.ode.events
  This interface represents a handler for discrete events triggered during ODE integration.
EventHandlerWithJacobians - Interface in org.apache.commons.math.ode.jacobians
  This interface represents a handler for discrete events triggered during ODE integration.
eventOccurred(double, double[], boolean) - Method in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
  Handle an event and choose what to do next.
eventOccurred(double, double[], boolean) - Method in interface org.apache.commons.math.ode.events.EventHandler
  Handle an event and choose what to do next.
eventOccurred(double, double[], double[][], double[][], boolean) - Method in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Handle an event and choose what to do next.
eventOccurred(double, double[], boolean) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Handle an event and choose what to do next.
eventsHandlersManager - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Events handlers manager.
EventState - Class in org.apache.commons.math.ode.events
  This class handles the state for one `event handler` during integration steps.
EventState(EventHandler, double, double, int) - Constructor for class org.apache.commons.math.ode.events.EventState
  Simple constructor.
evolve(Population, StoppingCondition) - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Evolve the given population.
EXACT_STIRLING_ERRORS - Static variable in class org.apache.commons.math.distribution.SaddlePointExpansion
  exact Stirling expansion error for certain values.
EXHAUSTED_ITERATOR_MESSAGE - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Message for exhausted iterator.
EXHAUSTED_ITERATOR_MESSAGE - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Message for exhausted iterator.
EXP - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.exp` method wrapped as a `ComposableFunction`.
exp() - Method in class org.apache.commons.math.complex.Complex
  Compute the exponential function of this complex number.
exp - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Stepsize control exponent.
exp - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Stepsize control exponent.
expand() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Expands the internal storage array using the expansion factor.
expandTo(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Expands the internal storage array to the specified size.
expansionFactor - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The expansion factor of the array.
expansionMode - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  Determines whether array expansion by `expansionFactor` is additive or multiplicative.
EXPM1 - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.expm1` method wrapped as a `ComposableFunction`.
exponent - Variable in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Exponent parameter of the distribution.
EXPONENTIAL_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Exponential random deviates with mean = μ.
ExponentialDistribution - Interface in org.apache.commons.math.distribution
  The Exponential Distribution.
ExponentialDistributionImpl - Class in org.apache.commons.math.distribution
  The default implementation of `ExponentialDistribution`.
ExponentialDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Create a exponential distribution with the given mean.
ExponentialDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Create a exponential distribution with the given mean.
extractField(T[][]) - Static method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Get the elements type from an array.
extractField(T[]) - Static method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Get the elements type from an array.
extrapolate(int, int, double[][], double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Extrapolate a vector.

## F

f - Variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Deprecated. as of 2.0 the integrand function is passed as an argument to the `UnivariateRealIntegrator.integrate(UnivariateRealFunction, double, double)`method.
f - Variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `UnivariateRealSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
f - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Objective function.
f - Variable in class org.apache.commons.math.optimization.fitting.CurveFitter.TheoreticalValuesFunction
  Function to fit.
f - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Linear objective function.
F - Variable in class org.apache.commons.math.stat.inference.OneWayAnovaImpl.AnovaStats
  Statistic.
factorial(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns n!.
factorialDouble(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns n!.
factorialLog(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the natural logarithm of n!.
FACTORIALS - Static variable in class org.apache.commons.math.util.MathUtils
  All long-representable factorials
FACTORY - Static variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils.LazyHolder
  Cached solver factory
FAILED_EVALUATION_MESSAGE - Static variable in exception org.apache.commons.math.FunctionEvaluationException
  Message for failed evaluation.
FastCosineTransformer - Class in org.apache.commons.math.transform
  Implements the Fast Cosine Transform for transformation of one-dimensional data sets.
FastCosineTransformer() - Constructor for class org.apache.commons.math.transform.FastCosineTransformer
  Construct a default transformer.
FastFourierTransformer - Class in org.apache.commons.math.transform
  Implements the Fast Fourier Transform for transformation of one-dimensional data sets.
FastFourierTransformer() - Constructor for class org.apache.commons.math.transform.FastFourierTransformer
  Construct a default transformer.
FastFourierTransformer.MultiDimensionalComplexMatrix - Class in org.apache.commons.math.transform
  Complex matrix implementation.
FastFourierTransformer.MultiDimensionalComplexMatrix(Object) - Constructor for class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Simple constructor.
FastFourierTransformer.RootsOfUnity - Class in org.apache.commons.math.transform
  Computes the nth roots of unity.
FastFourierTransformer.RootsOfUnity() - Constructor for class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Build an engine for computing then th roots of unity
FastHadamardTransformer - Class in org.apache.commons.math.transform
  Implements the Fast Hadamard Transform (FHT).
FastHadamardTransformer() - Constructor for class org.apache.commons.math.transform.FastHadamardTransformer
FastSineTransformer - Class in org.apache.commons.math.transform
  Implements the Fast Sine Transform for transformation of one-dimensional data sets.
FastSineTransformer() - Constructor for class org.apache.commons.math.transform.FastSineTransformer
  Construct a default transformer.
fct(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Perform the FCT algorithm (including inverse).
FDistribution - Interface in org.apache.commons.math.distribution
  F-Distribution.
FDistributionImpl - Class in org.apache.commons.math.distribution
  Default implementation of `FDistribution`.
FDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.FDistributionImpl
  Create a F distribution using the given degrees of freedom.
FDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.FDistributionImpl
  Create a F distribution using the given degrees of freedom and inverse cumulative probability accuracy.
fft(double[], boolean) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Perform the base-4 Cooley-Tukey FFT algorithm (including inverse).
fft(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Perform the base-4 Cooley-Tukey FFT algorithm (including inverse).
fht(double[]) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  The FHT (Fast Hadamard Transformation) which uses only subtraction and addition.
fht(int[]) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  The FHT (Fast Hadamard Transformation) which uses only subtraction and addition.
Field<T> - Interface in org.apache.commons.math
  Interface representing a field.
field - Variable in class org.apache.commons.math.linear.AbstractFieldMatrix
  Field to which the elements belong.
field - Variable in class org.apache.commons.math.linear.ArrayFieldVector
  Field to which the elements belong.
field - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Field to which the elements belong.
field - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Field to which the elements belong.
field - Variable in class org.apache.commons.math.linear.SparseFieldVector
  Field to which the elements belong.
field - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Field to which the elements belong.
FieldDecompositionSolver<T extends FieldElement<T>> - Interface in org.apache.commons.math.linear
  Interface handling decomposition algorithms that can solve A × X = B.
FieldElement<T> - Interface in org.apache.commons.math
  Interface representing field elements.
FieldLUDecomposition<T extends FieldElement<T>> - Interface in org.apache.commons.math.linear
  An interface to classes that implement an algorithm to calculate the LU-decomposition of a real matrix.
FieldLUDecompositionImpl<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Calculates the LUP-decomposition of a square matrix.
FieldLUDecompositionImpl(FieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Calculates the LU-decomposition of the given matrix.
FieldLUDecompositionImpl.Solver<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Specialized solver.
FieldLUDecompositionImpl.Solver(Field<T>, T[][], int[], boolean) - Constructor for class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Build a solver from decomposed matrix.
FieldMatrix<T extends FieldElement<T>> - Interface in org.apache.commons.math.linear
  Interface defining field-valued matrix with basic algebraic operations.
FieldMatrixChangingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math.linear
  Interface defining a visitor for matrix entries.
FieldMatrixPreservingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math.linear
  Interface defining a visitor for matrix entries.
FieldVector<T extends FieldElement<T>> - Interface in org.apache.commons.math.linear
  Interface defining a field-valued vector with basic algebraic operations.
filePointer - Variable in class org.apache.commons.math.random.ValueServer
  File pointer for REPLAY_MODE.
fill(double[]) - Method in class org.apache.commons.math.random.ValueServer
  Fills the input array with values generated using getNext() repeatedly.
fill(int) - Method in class org.apache.commons.math.random.ValueServer
  Returns an array of length `length` with values generated using getNext() repeatedly.
fill(double[], List<Integer>, double) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Sets`data[i] = value` for each i in `tiesTrace.`
fillBinStats(Object) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Fills binStats array (second pass through data file).
filterStep(double, boolean, boolean) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Filter the integration step.
finalized - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  indicate if the step has been finalized or not.
finalizeStep() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Finalize the step.
finalTime - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
  Final integration time.
findBin(double) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns the index of the bin to which the given value belongs
findEigenVectors(double[][]) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find eigenvalues and eigenvectors (Dubrulle et al., 1971)
findInsertionIndex(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Find the index at which a key should be inserted
findInsertionIndex(int[], byte[], int, int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Find the index at which a key should be inserted
findInsertionIndex(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Find the index at which a key should be inserted
findInsertionIndex(int[], byte[], int, int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Find the index at which a key should be inserted
findSameChromosome(Population) - Method in class org.apache.commons.math.genetics.Chromosome
  Searches the `population` for another chromosome with the same representation.
findUpperBound(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Find the upper bound b ensuring bracketing of a root between a and b
first - Variable in class org.apache.commons.math.genetics.ChromosomePair
  the first chromosome in the pair.
first - Variable in class org.apache.commons.math.ode.events.CombinedEventsManager
  First active event.
FirstMoment - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the first moment (arithmetic mean).
FirstMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Create a FirstMoment instance
FirstMoment(FirstMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Copy constructor, creates a new `FirstMoment` identical to the `original`
FirstOrderConverter - Class in org.apache.commons.math.ode
  This class converts second order differential equations to first order ones.
FirstOrderConverter(SecondOrderDifferentialEquations) - Constructor for class org.apache.commons.math.ode.FirstOrderConverter
  Simple constructor.
FirstOrderDifferentialEquations - Interface in org.apache.commons.math.ode
  This interface represents a first order differential equations set.
FirstOrderIntegrator - Interface in org.apache.commons.math.ode
  This interface represents a first order integrator for differential equations.
FirstOrderIntegratorWithJacobians - Class in org.apache.commons.math.ode.jacobians
  This class enhances a first order integrator for differential equations to compute also partial derivatives of the solution with respect to initial state and parameters.
FirstOrderIntegratorWithJacobians(FirstOrderIntegrator, ParameterizedODE, double[], double[], double[]) - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Build an enhanced integrator using internal differentiation to compute jacobians.
FirstOrderIntegratorWithJacobians(FirstOrderIntegrator, ODEWithJacobians) - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Build an enhanced integrator using ODE builtin jacobian computation features.
FirstOrderIntegratorWithJacobians.EventHandlerWrapper - Class in org.apache.commons.math.ode.jacobians
  Wrapper for event handlers.
FirstOrderIntegratorWithJacobians.EventHandlerWrapper(EventHandlerWithJacobians, int, int) - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Simple constructor.
FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper - Class in org.apache.commons.math.ode.jacobians
  Wrapper class to compute jacobians by finite differences for ODE which do not compute them themselves.
FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper(ParameterizedODE, double[], double[], double[]) - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Simple constructor.
FirstOrderIntegratorWithJacobians.MappingWrapper - Class in org.apache.commons.math.ode.jacobians
  Wrapper class used to map state and jacobians into compound state.
FirstOrderIntegratorWithJacobians.MappingWrapper() - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Simple constructor.
FirstOrderIntegratorWithJacobians.StepHandlerWrapper - Class in org.apache.commons.math.ode.jacobians
  Wrapper for step handlers.
FirstOrderIntegratorWithJacobians.StepHandlerWrapper(StepHandlerWithJacobians, int, int) - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Simple constructor.
FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper - Class in org.apache.commons.math.ode.jacobians
  Wrapper for step interpolators.
FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper() - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Simple constructor.
FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper(StepInterpolator, int, int) - Constructor for class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Simple constructor.
fit(ParametricRealFunction, double[]) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
  Fit a curve.
fit() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter
  Fit an harmonic function to the observed points.
fit() - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter
  Get the polynomial fitting the weighted (x, y) points.
fitness - Variable in class org.apache.commons.math.genetics.Chromosome
  Cached value of the fitness of this chromosome.
Fitness - Interface in org.apache.commons.math.genetics
  Fitness of a chromosome.
fitness() - Method in interface org.apache.commons.math.genetics.Fitness
  Compute the fitness.
fitter - Variable in class org.apache.commons.math.optimization.fitting.HarmonicFitter
  Fitter for the coefficients.
fitter - Variable in class org.apache.commons.math.optimization.fitting.PolynomialFitter
  Fitter for the coefficients.
fix1stArgument(double) - Method in class org.apache.commons.math.analysis.BinaryFunction
  Get a composable function by fixing the first argument of the instance.
fix2ndArgument(double) - Method in class org.apache.commons.math.analysis.BinaryFunction
  Get a composable function by fixing the second argument of the instance.
FixedGenerationCount - Class in org.apache.commons.math.genetics
  Stops after a fixed number of generations.
FixedGenerationCount(int) - Constructor for class org.apache.commons.math.genetics.FixedGenerationCount
  Create a new FixedGenerationCount instance.
FixedStepHandler - Interface in org.apache.commons.math.ode.sampling
  This interface represents a handler that should be called after each successful fixed step.
floatValue() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as a `float`.
floatValue() - Method in class org.apache.commons.math.fraction.Fraction
  Gets the fraction as a `float`.
FLOOR - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.floor` method wrapped as a `ComposableFunction`.
FORBIDDEN_ZERO_DENOMINATOR - Static variable in class org.apache.commons.math.fraction.BigFraction
  Message for zero denominator.
format(Complex, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Formats a `Complex` object to produce a string.
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Formats a object to produce a string.
format(double, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.AbstractFormat
  Formats a double value as a fraction and appends the result to a StringBuffer.
format(long, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.AbstractFormat
  Formats a long value as a fraction and appends the result to a StringBuffer.
format(BigFraction, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.BigFractionFormat
  Formats a `BigFraction` object to produce a string.
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.BigFractionFormat
  Formats an object and appends the result to a StringBuffer.
format(Fraction, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.FractionFormat
  Formats a `Fraction` object to produce a string.
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.FractionFormat
  Formats an object and appends the result to a StringBuffer.
format(BigFraction, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
  Formats a `BigFraction` object to produce a string.
format(Fraction, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.fraction.ProperFractionFormat
  Formats a `Fraction` object to produce a string.
format - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  The format used for components.
format(Vector3D, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Formats a `Vector3D` object to produce a string.
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Formats a object to produce a string.
format - Variable in class org.apache.commons.math.linear.RealVectorFormat
  The format used for components.
format(RealVector, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.linear.RealVectorFormat
  Formats a `RealVector` object to produce a string.
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.linear.RealVectorFormat
  Formats a object to produce a string.
formatBigFraction(BigFraction) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
  This static method calls formatBigFraction() on a default instance of BigFractionFormat.
formatComplex(Complex) - Static method in class org.apache.commons.math.complex.ComplexFormat
  This static method calls `Format.format(Object)` on a default instance of ComplexFormat.
formatDouble(double, NumberFormat, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.util.CompositeFormat
  Formats a double value to produce a string.
formatFraction(Fraction) - Static method in class org.apache.commons.math.fraction.FractionFormat
  This static method calls formatFraction() on a default instance of FractionFormat.
formatRealVector(RealVector) - Static method in class org.apache.commons.math.linear.RealVectorFormat
  This static method calls `Format.format(Object)` on a default instance of RealVectorFormat.
formatVector3D(Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3DFormat
  This static method calls `Format.format(Object)` on a default instance of Vector3DFormat.
forward - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
  Integration direction indicator.
forward - Variable in class org.apache.commons.math.ode.events.EventState
  Integration direction.
forward - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  integration direction.
forward - Variable in class org.apache.commons.math.ode.sampling.StepNormalizer
  Integration direction indicator.
FOUR_FIFTHS - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "4/5".
FOUR_FIFTHS - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "4/5".
FourthMoment - Class in org.apache.commons.math.stat.descriptive.moment
  Computes a statistic related to the Fourth Central Moment.
FourthMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Create a FourthMoment instance
FourthMoment(FourthMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Copy constructor, creates a new `FourthMoment` identical to the `original`
Fraction - Class in org.apache.commons.math.fraction
  Representation of a rational number.
Fraction(double) - Constructor for class org.apache.commons.math.fraction.Fraction
  Create a fraction given the double value.
Fraction(double, double, int) - Constructor for class org.apache.commons.math.fraction.Fraction
  Create a fraction given the double value and maximum error allowed.
Fraction(double, int) - Constructor for class org.apache.commons.math.fraction.Fraction
  Create a fraction given the double value and maximum denominator.
Fraction(double, double, int, int) - Constructor for class org.apache.commons.math.fraction.Fraction
  Create a fraction given the double value and either the maximum error allowed or the maximum number of denominator digits.
Fraction(int) - Constructor for class org.apache.commons.math.fraction.Fraction
  Create a fraction from an int.
Fraction(int, int) - Constructor for class org.apache.commons.math.fraction.Fraction
  Create a fraction given the numerator and denominator.
FractionConversionException - Exception in org.apache.commons.math.fraction
  Error thrown when a double value cannot be converted to a fraction in the allowed number of iterations.
FractionConversionException(double, int) - Constructor for exception org.apache.commons.math.fraction.FractionConversionException
  Constructs an exception with specified formatted detail message.
FractionConversionException(double, long, long) - Constructor for exception org.apache.commons.math.fraction.FractionConversionException
  Constructs an exception with specified formatted detail message.
FractionField - Class in org.apache.commons.math.fraction
  Representation of the fractional numbers field.
FractionField() - Constructor for class org.apache.commons.math.fraction.FractionField
  Private constructor for the singleton.
FractionField.LazyHolder - Class in org.apache.commons.math.fraction
  Holder for the instance.
FractionField.LazyHolder() - Constructor for class org.apache.commons.math.fraction.FractionField.LazyHolder
FractionFormat - Class in org.apache.commons.math.fraction
  Formats a Fraction number in proper format or improper format.
FractionFormat() - Constructor for class org.apache.commons.math.fraction.FractionFormat
  Create an improper formatting instance with the default number format for the numerator and denominator.
FractionFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.FractionFormat
  Create an improper formatting instance with a custom number format for both the numerator and denominator.
FractionFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.FractionFormat
  Create an improper formatting instance with a custom number format for the numerator and a custom number format for the denominator.
fractionMatrixToRealMatrix(FieldMatrix<Fraction>) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Convert a `FieldMatrix`/`Fraction` matrix to a `RealMatrix`.
FREE - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Status indicator for free table entries.
FREE - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Status indicator for free table entries.
freqTable - Variable in class org.apache.commons.math.stat.Frequency
  underlying collection
Frequency - Class in org.apache.commons.math.stat
  Maintains a frequency distribution.
Frequency() - Constructor for class org.apache.commons.math.stat.Frequency
  Default constructor.
Frequency(Comparator<?>) - Constructor for class org.apache.commons.math.stat.Frequency
  Constructor allowing values Comparator to be specified.
Frequency.NaturalComparator<T extends java.lang.Comparable<T>> - Class in org.apache.commons.math.stat
  A Comparator that compares comparable objects using the natural order.
Frequency.NaturalComparator() - Constructor for class org.apache.commons.math.stat.Frequency.NaturalComparator
fsal - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Indicator for fsal methods.
fst(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Perform the FST algorithm (including inverse).
FULL - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Status indicator for full table entries.
FULL - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Status indicator for full table entries.
function - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Objective function.
function - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Objective function.
function - Variable in class org.apache.commons.math.optimization.LeastSquaresConverter
  Underlying vectorial function.
function - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Linear objective function.
FunctionEvaluationException - Exception in org.apache.commons.math
  Exception thrown when an error occurs evaluating a function.
FunctionEvaluationException(double) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Construct an exception indicating the argument value that caused the function evaluation to fail.
FunctionEvaluationException(double[]) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Construct an exception indicating the argument value that caused the function evaluation to fail.
FunctionEvaluationException(double, String, Object...) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Constructs an exception with specified formatted detail message.
FunctionEvaluationException(double[], String, Object...) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Constructs an exception with specified formatted detail message.
FunctionEvaluationException(Throwable, double) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Constructs an exception with specified root cause.
FunctionEvaluationException(Throwable, double[]) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Constructs an exception with specified root cause.
FunctionEvaluationException(Throwable, double, String, Object...) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Constructs an exception with specified formatted detail message and root cause.
FunctionEvaluationException(Throwable, double[], String, Object...) - Constructor for exception org.apache.commons.math.FunctionEvaluationException
  Constructs an exception with specified formatted detail message and root cause.
functionValue - Variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Value of the function at the last computed result.
functionValue - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Value of the function at the last computed result.
functionValueAccuracy - Variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Maximum error of function.

## G

g(double, double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
  Compute the value of the switching function.
g(double, double[]) - Method in interface org.apache.commons.math.ode.events.EventHandler
  Compute the value of the switching function.
g(double, double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Compute the value of the switching function.
g(double, double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Compute the value of the switching function.
g0 - Variable in class org.apache.commons.math.ode.events.EventState
  Value of the events handler at the beginning of the step.
g0Positive - Variable in class org.apache.commons.math.ode.events.EventState
  Simulated sign of g0 (we cheat when crossing events).
gamma - Variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Internal Gamma distribution.
gamma - Variable in class org.apache.commons.math.optimization.direct.MultiDirectional
  Contraction coefficient.
gamma - Variable in class org.apache.commons.math.optimization.direct.NelderMead
  Contraction coefficient.
Gamma - Class in org.apache.commons.math.special
  This is a utility class that provides computation methods related to the Gamma family of functions.
Gamma() - Constructor for class org.apache.commons.math.special.Gamma
  Default constructor.
GAMMA - Static variable in class org.apache.commons.math.special.Gamma
  Euler-Mascheroni constant
GammaDistribution - Interface in org.apache.commons.math.distribution
  The Gamma Distribution.
GammaDistributionImpl - Class in org.apache.commons.math.distribution
  The default implementation of `GammaDistribution`.
GammaDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
  Create a new gamma distribution with the given alpha and beta values.
GammaDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
  Create a new gamma distribution with the given alpha and beta values.
GAUSSIAN_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Gaussian random deviates with mean = μ, std dev = σ.
GaussianRandomGenerator - Class in org.apache.commons.math.random
  This class is a gaussian normalized random generator for scalars.
GaussianRandomGenerator(RandomGenerator) - Constructor for class org.apache.commons.math.random.GaussianRandomGenerator
  Create a new generator.
GaussNewtonEstimator - Class in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
GaussNewtonEstimator() - Constructor for class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Simple constructor with default settings.
GaussNewtonEstimator(int, double, double) - Constructor for class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Simple constructor.
GaussNewtonOptimizer - Class in org.apache.commons.math.optimization.general
  Gauss-Newton least-squares solver.
GaussNewtonOptimizer(boolean) - Constructor for class org.apache.commons.math.optimization.general.GaussNewtonOptimizer
  Simple constructor with default settings.
gcd(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Gets the greatest common divisor of the absolute value of two numbers, using the "binary gcd" method which avoids division and modulo operations.
gcd(long, long) - Static method in class org.apache.commons.math.util.MathUtils
  Gets the greatest common divisor of the absolute value of two numbers, using the "binary gcd" method which avoids division and modulo operations.
generalizedHarmonic(int, double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Calculates the Nth generalized harmonic number.
generate(int) - Method in interface org.apache.commons.math.analysis.polynomials.PolynomialsUtils.RecurrenceCoefficientsGenerator
  Generate recurrence coefficients.
generationsEvolved - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  the number of generations evolved to reach `StoppingCondition` in the last run.
generator - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Random generator for multi-start.
generator - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Random generator for multi-start.
generator - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Random generator for multi-start.
generator - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Random generator for multi-start.
generator - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Underlying generator.
generator - Variable in class org.apache.commons.math.random.GaussianRandomGenerator
  Underlying generator.
generator - Variable in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
  Underlying scalar generator.
generator - Variable in class org.apache.commons.math.random.UniformRandomGenerator
  Underlying generator.
GeneticAlgorithm - Class in org.apache.commons.math.genetics
  Implementation of a genetic algorithm.
GeneticAlgorithm(CrossoverPolicy, double, MutationPolicy, double, SelectionPolicy) - Constructor for class org.apache.commons.math.genetics.GeneticAlgorithm
geoMean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  geoMean of values that have been added
geoMeanImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Geometric mean statistic implementation - can be reset by setter.
geoMeanImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Geometric mean statistic implementation - can be reset by setter.
GEOMETRIC_MEAN - Static variable in class org.apache.commons.math.stat.StatUtils
  geometric mean
GeometricMean - Class in org.apache.commons.math.stat.descriptive.moment
  Returns the geometric mean of the available values.
GeometricMean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Create a GeometricMean instance
GeometricMean(GeometricMean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Copy constructor, creates a new `GeometricMean` identical to the `original`
GeometricMean(SumOfLogs) - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Create a GeometricMean instance using the given SumOfLogs instance
geometricMean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the geometric mean of the entries in the input array, or `Double.NaN` if the array is empty.
geometricMean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the geometric mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
geometricMeanImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Geometric mean statistic implementation - can be reset by setter.
get(int...) - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Get a matrix element.
get(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Get the stored value associated with the given key
get(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Get the stored value associated with the given key
getA(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Access the n-th a coefficient of the continued fraction.
getA1() - Method in class org.apache.commons.math.geometry.RotationOrder
  Get the axis of the first rotation.
getA2() - Method in class org.apache.commons.math.geometry.RotationOrder
  Get the axis of the second rotation.
getA3() - Method in class org.apache.commons.math.geometry.RotationOrder
  Get the axis of the second rotation.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Get the actual absolute accuracy.
getAbsoluteAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Get the actual absolute accuracy.
getAbsoluteAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the actual absolute accuracy.
getAdapter(Object) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapterFactory
  Creates a DataAdapter from a data object
getAllParameters() - Method in interface org.apache.commons.math.estimation.EstimationProblem
  Deprecated. Get all the parameters of the problem.
getAllParameters() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Get all the parameters of the problem.
getAlpha() - Method in interface org.apache.commons.math.distribution.BetaDistribution
  Access the shape parameter, alpha
getAlpha() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Access the shape parameter, alpha
getAlpha() - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Access the shape parameter, alpha
getAlpha() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the shape parameter, alpha
getAlpha() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the azimuth of the vector.
getAmplitude() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Get the amplitude a.
getAngle() - Method in class org.apache.commons.math.geometry.Rotation
  Get the angle of the rotation.
getAngles(RotationOrder) - Method in class org.apache.commons.math.geometry.Rotation
  Get the Cardan or Euler angles corresponding to the instance.
getArgument() - Method in class org.apache.commons.math.complex.Complex
  Compute the argument of this complex number.
getArgument() - Method in exception org.apache.commons.math.FunctionEvaluationException
  Returns the function argument that caused this exception.
getArguments() - Method in exception org.apache.commons.math.MathException
  Gets the arguments used to build the message of this throwable.
getArguments() - Method in exception org.apache.commons.math.MathRuntimeException
  Gets the arguments used to build the message of this throwable.
getArity() - Method in class org.apache.commons.math.genetics.TournamentSelection
  Gets the arity (number of chromosomes drawn to the tournament).
getArray() - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Get the underlying storage array
getArtificialVariableOffset() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the offset of the first artificial variable.
getAvailableLocales() - Static method in class org.apache.commons.math.complex.ComplexFormat
  Get the set of locales for which complex formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
  Get the set of locales for which complex formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math.fraction.FractionFormat
  Get the set of locales for which complex formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math.geometry.Vector3DFormat
  Get the set of locales for which 3D vectors formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math.linear.RealVectorFormat
  Get the set of locales for which real vectors formats are available.
getAxis() - Method in class org.apache.commons.math.geometry.Rotation
  Get the normalized axis of the rotation.
getB() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Returns the bi-diagonal matrix B of the transform.
getB(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Access the n-th b coefficient of the continued fraction.
getBasicRow(int) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Checks whether the given column is basic.
getBeta() - Method in interface org.apache.commons.math.distribution.BetaDistribution
  Access the shape parameter, beta
getBeta() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Access the shape parameter, beta
getBeta() - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Access the scale parameter, beta
getBeta() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the scale parameter, beta
getBinCount() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns the number of bins.
getBinCount() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns the number of bins.
getBinStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns a list of `SummaryStatistics` containing statistics describing the values in each of the bins.
getBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns a List of `SummaryStatistics` instances containing statistics describing the values in each of the bins.
getCenter() - Method in class org.apache.commons.math.stat.clustering.Cluster
  Get the point chosen to be the center of this cluster.
getCenters() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Returns a copy of the centers array.
getChiSquare(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Get the Chi-Square value.
getChiSquare() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the Chi-Square value.
getChiSquareTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Return a (singleton) ChiSquareTest instance.
getChromosomes() - Method in class org.apache.commons.math.genetics.ListPopulation
  Access the list of chromosomes.
getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
  Get the coefficients of the constraint (left hand side).
getCoefficients() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Get the coefficients of the linear equation being optimized.
getColumn(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entries in column number `col` as an array.
getColumn(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entries in column number `col` as an array.
getColumn(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in column number `col` as an array.
getColumnAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entries in column number `col` as an array of double values.
getColumnAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entries in column number `col` as an array of double values.
getColumnDimension() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in interface org.apache.commons.math.linear.AnyMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Returns the number of columns in the matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnVector(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entries in column number `column` as a vector.
getColumnVector(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entries in column number `column` as a vector.
getColumnVector(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entries in column number `column` as a vector.
getColumnVector(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entries in column number `column` as a vector.
getColumnVector(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entries in column number `column` as a vector.
getColumnVector(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in column number `column` as a vector.
getConditionNumber() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Return the condition number of the matrix.
getConditionNumber() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Return the condition number of the matrix.
getConstantTerm() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Get the constant of the linear equation being optimized.
getConstraintTypeCounts(Relationship) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get a count of constraints corresponding to a specified relationship.
getContents() - Method in class org.apache.commons.math.MessagesResources_fr
  Get the non-translated/translated messages arrays from this resource bundle.
getContractionCriteria() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  The contraction criteria defines when the internal array will contract to store only the number of elements in the element array.
getConvergence() - Method in class org.apache.commons.math.ode.events.EventState
  Get the convergence threshold for event localization.
getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Get the convergence checker.
getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Get the convergence checker.
getConvertedMatrix() - Method in class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
  Get the converted matrix.
getConvertedMatrix() - Method in class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
  Get the converted matrix.
getCorrelationMatrix() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Returns the correlation matrix
getCorrelationMatrix() - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Calculate the Spearman Rank Correlation Matrix.
getCorrelationPValues() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Returns a matrix of p-values associated with the (two-sided) null hypothesis that the corresponding correlation coefficient is zero.
getCorrelationStandardErrors() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Returns a matrix of standard errors associated with the estimates in the correlation matrix.
  `getCorrelationStandardErrors().getEntry(i,j)` is the standard error associated with `getCorrelationMatrix.getEntry(i,j)`
getCostEvaluations() - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Get the number of cost evaluations.
getCount(Object) - Method in class org.apache.commons.math.stat.Frequency
  Deprecated. replaced by `Frequency.getCount(Comparable)` as of 2.0
getCount(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCount(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCount(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCount(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCovariance(double) - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the n × n covariance matrix.
getCovariance(double) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the n × n covariance matrix.
getCovariance() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the covariance matrix of the values that have been added.
getCovariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns the covariance of the available values.
getCovariance() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the covariance matrix of the values that have been added.
getCovarianceMatrix() - Method in class org.apache.commons.math.stat.correlation.Covariance
  Returns the covariance matrix
getCovariances(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Get the covariance matrix of unbound estimated parameters.
getCovariances(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
  Deprecated. Get the covariance matrix of estimated parameters.
getCovariances() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the covariance matrix of optimized parameters.
getCrossoverPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the crossover policy.
getCrossoverRate() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the crossover rate.
getCumFreq(Object) - Method in class org.apache.commons.math.stat.Frequency
  Deprecated. replaced by `Frequency.getCumFreq(Comparable)` as of 2.0
getCumFreq(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumFreq(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumFreq(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumFreq(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumPct(Object) - Method in class org.apache.commons.math.stat.Frequency
  Deprecated. replaced by `Frequency.getCumPct(Comparable)` as of 2.0
getCumPct(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCumPct(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCumPct(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCumPct(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCurrentSignedStepsize() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get the current signed value of the integration stepsize.
getCurrentStepStart() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get the current value of the step start time ti.
getCurrentStepStart() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Get the current value of the step start time ti.
getCurrentStepStart() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Get the current value of the step start time ti.
getCurrentStepStart() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get the current value of the step start time ti.
getCurrentTime() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the current grid point time.
getCurrentTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the current grid point time.
getCurrentTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Get the current grid point time.
getCurrentTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Get the current grid point time.
getD() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns the block diagonal matrix D of the decomposition.
getD() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns the block diagonal matrix D of the decomposition.
getData() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Returns vector entries as a double array.
getData() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Returns vector entries as a T array.
getData() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns vector entries as a double array.
getData() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math.linear.FieldVector
  Returns vector entries as a T array.
getData() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Returns vector entries as a double array.
getData() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math.linear.RealVector
  Returns vector entries as a double array.
getData() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Returns vector entries as a T array.
getData() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the tableau data.
getDataAsDoubleArray() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns matrix entries as a two-dimensional array.
getDataAsDoubleArray() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns matrix entries as a two-dimensional array.
getDataRef() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns a reference to the underlying data array.
getDefaultNumberFormat() - Static method in class org.apache.commons.math.fraction.AbstractFormat
  Create a default number format.
getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math.fraction.AbstractFormat
  Create a default number format.
getDefaultNumberFormat() - Static method in class org.apache.commons.math.fraction.FractionFormat
  Create a default number format.
getDefaultNumberFormat() - Static method in class org.apache.commons.math.util.CompositeFormat
  Create a default number format.
getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math.util.CompositeFormat
  Create a default number format.
getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
  Access the degrees of freedom.
getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the degrees of freedom.
getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.TDistribution
  Access the degrees of freedom.
getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the degrees of freedom.
getDelta() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the elevation of the vector.
getDenominator() - Method in class org.apache.commons.math.fraction.BigFraction
  Access the denominator as a `BigInteger`.
getDenominator() - Method in class org.apache.commons.math.fraction.Fraction
  Access the denominator.
getDenominatorAsInt() - Method in class org.apache.commons.math.fraction.BigFraction
  Access the denominator as a `int`.
getDenominatorAsLong() - Method in class org.apache.commons.math.fraction.BigFraction
  Access the denominator as a `long`.
getDenominatorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
  Access the denominator degrees of freedom.
getDenominatorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the denominator degrees of freedom.
getDenominatorFormat() - Method in class org.apache.commons.math.fraction.AbstractFormat
  Access the denominator format.
getDeterminant() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated.
getDeterminant() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the determinant of this matrix.
getDeterminant() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the determinant of this matrix.
getDeterminant() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
  Return the determinant of the matrix
getDeterminant() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Return the determinant of the matrix
getDeterminant() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Return the determinant of the matrix
getDeterminant() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Return the determinant of the matrix
getDeterminant() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
  Return the determinant of the matrix
getDeterminant() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Return the determinant of the matrix
getDeterminant() - Method in interface org.apache.commons.math.linear.LUDecomposition
  Return the determinant of the matrix
getDeterminant() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
  Return the determinant of the matrix
getDeterminant() - Method in interface org.apache.commons.math.linear.RealMatrix
  Deprecated. as of release 2.0, replaced by ``new LUDecompositionImpl(m)`.`getDeterminant()``
getDeviancePart(double, double) - Static method in class org.apache.commons.math.distribution.SaddlePointExpansion
  A part of the deviance portion of the saddle point approximation.
getDimension() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns the size of the vector.
getDimension() - Method in interface org.apache.commons.math.linear.FieldVector
  Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Returns the size of the vector.
getDimension() - Method in interface org.apache.commons.math.linear.RealVector
  Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math.ode.FirstOrderConverter
  Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math.ode.FirstOrderDifferentialEquations
  Get the dimension of the problem.
getDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Get the dimension of the problem.
getDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Get the dimension of the problem.
getDimension() - Method in class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
  Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math.ode.SecondOrderDifferentialEquations
  Get the dimension of the problem.
getDimension() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the dimension of the data
getDimension() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns the dimension of the data
getDimension() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the dimension of the data
getDimension1() - Method in exception org.apache.commons.math.DimensionMismatchException
  Get the first dimension
getDimension2() - Method in exception org.apache.commons.math.DimensionMismatchException
  Get the second dimension
getDimensionSizes() - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Get the size in all dimensions.
getDirection() - Method in enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
  Returns the value of this Direction.
getDistance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Distance between two vectors.
getDistance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Distance between two vectors.
getDistance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getDistance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getDistance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getDistance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to compute distance.
getDistance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getDistance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getDistance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Distance between two vectors.
getDistance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Distance between two vectors.
getDomain(int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Return the domain for the given hypergeometric distribution parameters.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDuplicateAbscissa() - Method in exception org.apache.commons.math.DuplicateSampleAbscissaException
  Get the duplicate abscissa.
getEigenvector(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns a copy of the ith eigenvector of the original matrix.
getEigenvector(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns a copy of the ith eigenvector of the original matrix.
getElement(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the element at the specified index
getElement(int) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Returns the element at the specified index
getElement(int) - Method in interface org.apache.commons.math.util.DoubleArray
  Returns the element at the specified index.
getElement(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the element at the specified index
getElements() - Method in interface org.apache.commons.math.util.DoubleArray
  Returns a double[] array containing the elements of this `DoubleArray`.
getElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns a double array containing the elements of this `ResizableArray`.
getElitismRate() - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
  Access the elitism rate.
getEmpiricalDistribution() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property empiricalDistribution.
getEntries() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Get the entries of this instance.
getEntries() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Get the entries of this instance.
getEntry(int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the entry in the specified row and column.
getEntry(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Returns the entry in the specified index.
getEntry(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns the entry in the specified index.
getEntry(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entry in the specified row and column.
getEntry(int) - Method in interface org.apache.commons.math.linear.FieldVector
  Returns the entry in the specified index.
getEntry(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Returns the entry in the specified row and column.
getEntry(int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Returns the entry in the specified index.
getEntry(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the entry in the specified row and column.
getEntry(int) - Method in interface org.apache.commons.math.linear.RealVector
  Returns the entry in the specified index.
getEntry(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Returns the entry in the specified row and column.
getEntry(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Returns the entry in the specified index.
getEntry(int, int) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get an entry of the tableau.
getEntryAsDouble(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entry in the specified row and column as a double.
getEntryAsDouble(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entry in the specified row and column as a double.
getEstimate() - Method in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Get the current estimate of the parameter
getEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get the number of evaluations of the differential equations function.
getEvaluations() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Get the number of evaluations of the differential equations function.
getEvaluations() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get the number of evaluations of the differential equations function.
getEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEvaluations() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Get the number of evaluations of the objective function.
getEventHandler() - Method in class org.apache.commons.math.ode.events.EventState
  Get the underlying event handler.
getEventHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get all the event handlers that have been added to the integrator.
getEventHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Get all the event handlers that have been added to the integrator.
getEventHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get all the event handlers that have been added to the integrator.
getEventsHandlers() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Get all the events handlers that have been added to the manager.
getEventsStates() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Get all the events state wrapping the handlers that have been added to the manager.
getEventTime() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Get the occurrence time of the first event triggered in the last evaluated step.
getEventTime() - Method in class org.apache.commons.math.ode.events.EventState
  Get the occurrence time of the event triggered in the current step.
getExpansionFactor() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  The expansion factor controls the size of a new array when an array needs to be expanded.
getExpansionMode() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  The `expansionMode` determines whether the internal storage array grows additively (ADDITIVE_MODE) or multiplicatively (MULTIPLICATIVE_MODE) when it is expanded.
getExponent() - Method in interface org.apache.commons.math.distribution.ZipfDistribution
  Get the exponent characterising the distribution.
getExponent() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Get the exponent characterising the distribution.
getField() - Method in class org.apache.commons.math.complex.Complex
  Get the `Field` to which the instance belongs.
getField() - Method in interface org.apache.commons.math.FieldElement
  Get the `Field` to which the instance belongs.
getField() - Method in class org.apache.commons.math.fraction.BigFraction
  Get the `Field` to which the instance belongs.
getField() - Method in class org.apache.commons.math.fraction.Fraction
  Get the `Field` to which the instance belongs.
getField() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Get the type of field elements of the matrix.
getField() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Get the type of field elements of the vector.
getField() - Method in interface org.apache.commons.math.linear.FieldMatrix
  Get the type of field elements of the matrix.
getField() - Method in interface org.apache.commons.math.linear.FieldVector
  Get the type of field elements of the vector.
getField() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Get the type of field elements of the vector.
getField() - Method in class org.apache.commons.math.util.BigReal
  Get the `Field` to which the instance belongs.
getFinalTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Get the final integration time.
getFirst() - Method in class org.apache.commons.math.genetics.ChromosomePair
  Access the first chromosome.
getFitness() - Method in class org.apache.commons.math.genetics.Chromosome
  Access the fitness of this chromosome.
getFittestChromosome() - Method in class org.apache.commons.math.genetics.ListPopulation
  Access the fittest chromosome in this population.
getFittestChromosome() - Method in interface org.apache.commons.math.genetics.Population
  Access the fittest chromosome in this population.
getFormat() - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Get the components format.
getFormat() - Method in class org.apache.commons.math.linear.RealVectorFormat
  Get the components format.
getFrobeniusNorm() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the Frobenius norm of the matrix.
getFrobeniusNorm() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the Frobenius norm of the matrix.
getFrobeniusNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the Frobenius norm of the matrix.
getFunctionValue() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Get the result of the last run of the solver.
getFunctionValue() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Get the result of the last run of the solver.
getFunctionValue() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the result of the last run of the optimizer.
getFunctionValue() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Get the result of the last run of the optimizer.
getFunctionValue() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Get the result of the last run of the optimizer.
getFunctionValueAccuracy() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Get the actual function value accuracy.
getFunctionValueAccuracy() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Get the actual function value accuracy.
getGenerationsEvolved() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the number of generations evolved to reach `StoppingCondition` in the last run.
getGenerator() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Get the underlying normalized components generator.
getGeneratorUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns a fresh copy of the array of upper bounds of the subintervals of [0,1] used in generating data from the empirical distribution.
getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured geometric mean implementation
getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured geometric mean implementation
getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured geometric mean implementation
getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured geometric mean implementation
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the geometric mean of all the aggregated data.
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the geometric mean of the available values
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getGeometricMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that correspond to each multivariate sample
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the geometric mean of the values that have been added.
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the geometric mean of the values that have been added.
getGeometricMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured geometric mean implementation.
getGradientEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Get the number of evaluations of the objective function gradient.
getGradientEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Get the number of evaluations of the objective function gradient.
getGradientEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get the number of evaluations of the objective function gradient.
getGuessedAmplitude() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Get the guessed amplitude a.
getGuessedPhase() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Get the guessed phase φ.
getGuessedPulsation() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Get the guessed pulsation ω.
getH() - Method in interface org.apache.commons.math.linear.QRDecomposition
  Returns the Householder reflector vectors.
getH() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
  Returns the Householder reflector vectors.
getHandler() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Get the underlying event handler with jacobians.
getHandler() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Get the underlying step handler with jacobians.
getHeight() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the height of the tableau.
getHouseholderVectorsRef() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Get the Householder vectors of the transform.
getHouseholderVectorsRef() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Get the Householder vectors of the transform.
getImagEigenvalue(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns the imaginary part of the ith eigenvalue of the original matrix.
getImagEigenvalue(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns the imaginary part of the ith eigenvalue of the original matrix.
getImagEigenvalues() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns a copy of the imaginary parts of the eigenvalues of the original matrix.
getImagEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns a copy of the imaginary parts of the eigenvalues of the original matrix.
getImaginary() - Method in class org.apache.commons.math.complex.Complex
  Access the imaginary part.
getImaginaryCharacter() - Method in class org.apache.commons.math.complex.ComplexFormat
  Access the imaginaryCharacter.
getImaginaryFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
  Access the imaginaryFormat.
getImproperInstance() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
  Returns the default complex format for the current locale.
getImproperInstance(Locale) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
  Returns the default complex format for the given locale.
getImproperInstance() - Static method in class org.apache.commons.math.fraction.FractionFormat
  Returns the default complex format for the current locale.
getImproperInstance(Locale) - Static method in class org.apache.commons.math.fraction.FractionFormat
  Returns the default complex format for the given locale.
getIndex() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
  Get the index of the entry.
getIndex() - Method in class org.apache.commons.math.linear.RealVector.Entry
  Get the index of the entry.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Get the initial integration time.
getInstance() - Static method in class org.apache.commons.math.complex.ComplexField
  Get the unique instance.
getInstance() - Static method in class org.apache.commons.math.complex.ComplexFormat
  Returns the default complex format for the current locale.
getInstance(Locale) - Static method in class org.apache.commons.math.complex.ComplexFormat
  Returns the default complex format for the given locale.
getInstance() - Static method in class org.apache.commons.math.fraction.BigFractionField
  Get the unique instance.
getInstance() - Static method in class org.apache.commons.math.fraction.FractionField
  Get the unique instance.
getInstance() - Static method in class org.apache.commons.math.geometry.Vector3DFormat
  Returns the default 3D vector format for the current locale.
getInstance(Locale) - Static method in class org.apache.commons.math.geometry.Vector3DFormat
  Returns the default 3D vector format for the given locale.
getInstance() - Static method in class org.apache.commons.math.linear.RealVectorFormat
  Returns the default real vector format for the current locale.
getInstance(Locale) - Static method in class org.apache.commons.math.linear.RealVectorFormat
  Returns the default real vector format for the given locale.
getInstance(int) - Static method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Get the Nordsieck transformer for a given number of steps.
getInstance() - Static method in class org.apache.commons.math.ode.sampling.DummyStepHandler
  Get the only instance.
getInstance() - Static method in class org.apache.commons.math.util.BigRealField
  Get the unique instance.
getIntercept() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the intercept of the estimated regression line.
getIntercept(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the intercept of the estimated regression line, given the slope.
getInterceptStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the standard error of the intercept estimate, usually denoted s(b0).
getInternalLength() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Notice the package scope on this method.
getInternalValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the internal storage array.
getInterpolatedDerivatives() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Get the derivatives of the state vector of the interpolated point.
getInterpolatedDerivatives() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Get the derivatives of the state vector of the interpolated point.
getInterpolatedDyDp() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the partial derivatives of the state vector with respect to the ODE parameters of the interpolated point.
getInterpolatedDyDp() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the partial derivatives of the state vector with respect to the ODE parameters of the interpolated point.
getInterpolatedDyDpDot() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the time derivatives of the jacobian of the state vector with respect to the ODE parameters of the interpolated point.
getInterpolatedDyDpDot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the time derivatives of the jacobian of the state vector with respect to the ODE parameters of the interpolated point.
getInterpolatedDyDy0() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the partial derivatives of the state vector with respect to the initial state of the interpolated point.
getInterpolatedDyDy0() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the partial derivatives of the state vector with respect to the initial state of the interpolated point.
getInterpolatedDyDy0Dot() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the time derivatives of the jacobian of the state vector with respect to the initial state of the interpolated point.
getInterpolatedDyDy0Dot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the time derivatives of the jacobian of the state vector with respect to the initial state of the interpolated point.
getInterpolatedState() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Get the state vector of the interpolated point.
getInterpolatedState() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Get the state vector of the interpolated point.
getInterpolatedState() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Get the state vector of the interpolated point.
getInterpolatedStateVariation() - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Get the state vector variation from current to interpolated state.
getInterpolatedTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Get the time of the interpolated point.
getInterpolatedTime() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the time of the interpolated point.
getInterpolatedTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the time of the interpolated point.
getInterpolatedTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Get the time of the interpolated point.
getInterpolatedTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Get the time of the interpolated point.
getInterpolatedY() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the state vector of the interpolated point.
getInterpolatedY() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the state vector of the interpolated point.
getInterpolatedYDot() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the time derivatives of the state vector of the interpolated point.
getInterpolatedYDot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the time derivatives of the state vector of the interpolated point.
getInterpolatingPoints() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Returns a copy of the interpolating points array.
getInterpolatingValues() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Returns a copy of the interpolating values array.
getInverse() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverse() - Method in interface org.apache.commons.math.linear.DecompositionSolver
  Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverse() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Get the inverse of the decomposed matrix.
getInverse() - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
  Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverse() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverse() - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverse() - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverse() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Get the pseudo-inverse of the decomposed matrix.
getInvertedCoeffiecientSum(RealVector) - Static method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the -1 times the sum of all coefficients in the given array.
getIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Get the number of iterations in the last run of the algorithm.
getIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Get the number of iterations in the last run of the algorithm.
getIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the number of iterations in the last run of the algorithm.
getIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Get the number of iterations realized by the algorithm.
getIterations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Get the number of iterations realized by the algorithm.
getJacobianEvaluations() - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Get the number of jacobian evaluations.
getJacobianEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Get the number of evaluations of the objective function jacobian .
getJacobianEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the number of evaluations of the objective function jacobian .
getJacobianEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get the number of evaluations of the objective function jacobian .
getKnots() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Returns an array copy of the knot points.
getKurtosis() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the Kurtosis of the available values.
getKurtosisImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured kurtosis implementation.
getL() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
  Returns the matrix L of the decomposition.
getL() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Returns the matrix L of the decomposition.
getL() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
  Returns the matrix L of the decomposition.
getL() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Returns the matrix L of the decomposition.
getL() - Method in interface org.apache.commons.math.linear.LUDecomposition
  Returns the matrix L of the decomposition.
getL() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
  Returns the matrix L of the decomposition.
getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Distance between two vectors.
getL1Distance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Distance between two vectors.
getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getL1Distance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getL1Distance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getL1Distance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getL1Distance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getL1Distance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Distance between two vectors.
getL1Distance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Distance between two vectors.
getL1Norm() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Returns the L1 norm of the vector.
getL1Norm() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns the L1 norm of the vector.
getL1Norm() - Method in interface org.apache.commons.math.linear.RealVector
  Returns the L1 norm of the vector.
getLength() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
  Returns the length of the chromosome.
getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Distance between two vectors.
getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Distance between two vectors.
getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getLInfDistance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Distance between two vectors.
getLInfDistance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to compute LInfDistance.
getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Distance between two vectors.
getLInfDistance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Distance between two vectors.
getLInfDistance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Distance between two vectors.
getLInfNorm() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Returns the L∞ norm of the vector.
getLInfNorm() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns the L∞ norm of the vector.
getLInfNorm() - Method in interface org.apache.commons.math.linear.RealVector
  Returns the L∞ norm of the vector.
getLocalizedMessage() - Method in exception org.apache.commons.math.MathException
getLocalizedMessage() - Method in exception org.apache.commons.math.MathRuntimeException
getLowerDomain(int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Return the lowest domain value for the given hypergeometric distribution parameters.
getLT() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
  Returns the transpose of the matrix L of the decomposition.
getLT() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Returns the transpose of the matrix L of the decomposition.
getLUMatrix() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the LU decomposition as a BigMatrix.
getMainDiagonalRef() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Get the main diagonal elements of the matrix B of the transform.
getMainDiagonalRef() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Get the main diagonal elements of the matrix T of the transform.
getMatrix() - Method in class org.apache.commons.math.geometry.Rotation
  Get the 3X3 matrix corresponding to the instance
getMax() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the maximum of the available values
getMax() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the maximum of the available values
getMax() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the maximum of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the maximum of the ith entries of the arrays that correspond to each multivariate sample
getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the maximum of the available values
getMax() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getMax() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the maximum of the values that have been added.
getMax() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the maximum of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getMax() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the maximum of the values that have been added.
getMaxCheckInterval() - Method in class org.apache.commons.math.ode.events.EventState
  Get the maximal time interval between events handler checks.
getMaxEvaluations() - Method in exception org.apache.commons.math.MaxEvaluationsExceededException
  Get the maximal number of evaluations allowed.
getMaxEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Get the maximal number of functions evaluations.
getMaxGrowth() - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Get the maximal growth factor for stepsize control.
getMaxGrowth() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Get the maximal growth factor for stepsize control.
getMaximalIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Get the upper limit for the number of iterations.
getMaximalIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Get the upper limit for the number of iterations.
getMaximalIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the upper limit for the number of iterations.
getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured maximum implementation.
getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured maximum implementation
getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured maximum implementation
getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured maximum implementation
getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured maximum implementation
getMaxIndex() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Get the index of the maximum entry.
getMaxIterationCount() - Method in class org.apache.commons.math.ode.events.EventState
  Get the upper limit in the iteration count for event localization.
getMaxIterations() - Method in exception org.apache.commons.math.MaxIterationsExceededException
  Get the maximal number of iterations allowed.
getMaxIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxIterations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Get the maximal number of iterations of the algorithm.
getMaxStep() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Get the maximal step.
getMaxValue() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Get the value of the maximum entry.
getMean() - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
  Access the mean.
getMean() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the mean.
getMean() - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Access the mean.
getMean() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the mean.
getMean() - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Get the mean for the distribution.
getMean() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Get the Poisson mean for the distribution.
getMean() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the arithmetic mean of the available values
getMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the arithmetic mean of the available values
getMean() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the mean of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the mean of the ith entries of the arrays that correspond to each multivariate sample
getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the arithmetic mean of the available values
getMean() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the mean of the values that have been added.
getMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the mean of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the mean of the values that have been added.
getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured mean implementation.
getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured mean implementation
getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured mean implementation
getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured mean implementation
getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured mean implementation
getMeanSquareError() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared errors divided by the degrees of freedom, usually abbreviated MSE.
getMeasuredValue() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Get the measured value
getMeasurements() - Method in interface org.apache.commons.math.estimation.EstimationProblem
  Deprecated. Get the measurements of an estimation problem.
getMeasurements() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Get the measurements of an estimation problem.
getMedian() - Method in interface org.apache.commons.math.distribution.CauchyDistribution
  Access the median.
getMedian() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Access the median.
getMessage(Locale) - Method in exception org.apache.commons.math.MathException
  Gets the message in a specified locale.
getMessage() - Method in exception org.apache.commons.math.MathException
getMessage(Locale) - Method in exception org.apache.commons.math.MathRuntimeException
  Gets the message in a specified locale.
getMessage() - Method in exception org.apache.commons.math.MathRuntimeException
getMin() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the minimum of the available values
getMin() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the minimum of the available values
getMin() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the minimum of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the minimum of the ith entries of the arrays that correspond to each multivariate sample
getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the minimum of the available values
getMin() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getMin() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the minimum of the values that have been added.
getMin() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the minimum of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getMin() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the minimum of the values that have been added.
getMinimalIterationCount() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
  Get the lower limit for the number of iterations.
getMinimalIterationCount() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Get the lower limit for the number of iterations.
getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured minimum implementation.
getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured minimum implementation
getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured minimum implementation
getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured minimum implementation
getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured minimum implementation
getMinIndex() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Get the index of the minimum entry.
getMinReduction() - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Get the minimal reduction factor for stepsize control.
getMinReduction() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Get the minimal reduction factor for stepsize control.
getMinStep() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Get the minimal step.
getMinValue() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Get the value of the minimum entry.
getMode() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property mode.
getMu() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property mu.
getMutationPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the mutation policy.
getMutationRate() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the mutation rate.
getN() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Returns the number of spline segments = the number of polynomials = the number of knot points - 1.
getN() - Method in class org.apache.commons.math.stat.correlation.Covariance
  Returns the number of observations (length of covariate vectors)
getN() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Get the number of vectors in the sample.
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
  Get the number of vectors in the sample.
getN() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Returns the number of values that have been added.
getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns the number of available values
getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getN() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the number of observations that have been added to the model.
getName() - Method in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. get the name of the parameter
getName() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get the name of the method.
getName() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get the name of the method.
getNanPositions(NaturalRanking.IntDoublePair[]) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Returns a list of indexes where `ranks` is `NaN.`
getNanStrategy() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Return the NaNStrategy
getNatural(int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Returns an array representing n.
getNearestCluster(Collection<Cluster<T>>, T) - Static method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
  Returns the nearest `Cluster` to the given point
getNewtonCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Returns a copy of coefficients in Newton form formula.
getNext() - Method in class org.apache.commons.math.random.ValueServer
  Returns the next generated value, generated according to the mode value (see MODE constants).
getNextDigest() - Method in class org.apache.commons.math.random.ValueServer
  Gets a random value in DIGEST_MODE.
getNextExponential() - Method in class org.apache.commons.math.random.ValueServer
  Gets an exponentially distributed random value with mean = mu.
getNextGaussian() - Method in class org.apache.commons.math.random.ValueServer
  Gets a Gaussian distributed random value with mean = mu and standard deviation = sigma.
getNextReplay() - Method in class org.apache.commons.math.random.ValueServer
  Gets next sequential value from the `valuesFileURL`.
getNextUniform() - Method in class org.apache.commons.math.random.ValueServer
  Gets a uniformly distributed random value with mean = mu.
getNextValue() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Generates a random value from this distribution.
getNextValue() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Generates a random value from this distribution.
getNorm() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the L2 norm for the vector.
getNorm() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Returns the L2 norm of the vector.
getNorm() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns the L2 norm of the vector.
getNorm() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in interface org.apache.commons.math.linear.RealVector
  Returns the L2 norm of the vector.
getNorm() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the L2 norm of the matrix.
getNorm() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the L2 norm of the matrix.
getNorm1() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the L1 norm for the vector.
getNormInf() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the L∞ norm for the vector.
getNormSq() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the square of the norm for the vector.
getNSteps() - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Get the number of steps of the method (excluding the one being computed).
getNumArtificialVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the number of artificial variables.
getNumberOfElements() - Method in interface org.apache.commons.math.distribution.ZipfDistribution
  Get the number of elements (e.g.
getNumberOfElements() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Get the number of elements (e.g.
getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Access the number of successes.
getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the number of successes.
getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.PascalDistribution
  Access the number of successes for this distribution.
getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Access the number of successes for this distribution.
getNumberOfTrials() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Access the number of trials for this distribution.
getNumberOfTrials() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the number of trials for this distribution.
getNumDecisionVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the number of decision variables.
getNumElements() - Method in interface org.apache.commons.math.util.DoubleArray
  Returns the number of elements currently in the array.
getNumElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the number of elements currently in the array.
getNumerator() - Method in class org.apache.commons.math.fraction.BigFraction
  Access the numerator as a `BigInteger`.
getNumerator() - Method in class org.apache.commons.math.fraction.Fraction
  Access the numerator.
getNumeratorAsInt() - Method in class org.apache.commons.math.fraction.BigFraction
  Access the numerator as a `int`.
getNumeratorAsLong() - Method in class org.apache.commons.math.fraction.BigFraction
  Access the numerator as a `long`.
getNumeratorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
  Access the numerator degrees of freedom.
getNumeratorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the numerator degrees of freedom.
getNumeratorFormat() - Method in class org.apache.commons.math.fraction.AbstractFormat
  Access the numerator format.
getNumGenerations() - Method in class org.apache.commons.math.genetics.FixedGenerationCount
getNumObjectiveFunctions() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the number of objective functions in this tableau.
getNumSlackVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the number of slack variables.
getObservations() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
  Get the observed points.
getOmegaImaginary(int) - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Get the imaginary part of the kth nth root of unity
getOmegaInverse() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Get the inverse of the covariance.
getOmegaReal(int) - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Get the real part of the kth nth root of unity
getOne() - Method in class org.apache.commons.math.complex.ComplexField
  Get the multiplicative identity of the field.
getOne() - Method in interface org.apache.commons.math.Field
  Get the multiplicative identity of the field.
getOne() - Method in class org.apache.commons.math.fraction.BigFractionField
  Get the multiplicative identity of the field.
getOne() - Method in class org.apache.commons.math.fraction.FractionField
  Get the multiplicative identity of the field.
getOne() - Method in class org.apache.commons.math.util.BigRealField
  Get the multiplicative identity of the field.
getOneWayAnova() - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Return a (singleton) OneWayAnova instance.
getOptima() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Get all the optima found during the last call to `optimize`.
getOptima() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Get all the optima found during the last call to `optimize`.
getOptima() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Get all the optima found during the last call to `optimize`.
getOptima() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get all the optima found during the last call to `optimize`.
getOptimaValues() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get all the function values at optima found during the last call to `optimize`.
getOrder() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Get the order of the method.
getOrder() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Get the order of the method.
getOrder() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Get the order of the method.
getOrder() - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Get the order of the method.
getOriginalNumDecisionVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the original number of decision variables.
getP() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
  Returns the P rows permutation matrix.
getP() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Returns the P rows permutation matrix.
getP() - Method in interface org.apache.commons.math.linear.LUDecomposition
  Returns the P rows permutation matrix.
getP() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
  Returns the P rows permutation matrix.
getParametersDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Get the number of parameters.
getParametersDimension() - Method in interface org.apache.commons.math.ode.jacobians.ODEWithJacobians
  Get the number of parameters.
getParametersDimension() - Method in interface org.apache.commons.math.ode.jacobians.ParameterizedODE
  Get the number of parameters.
getPartial(EstimatedParameter) - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Get the partial derivative of the `theoretical value` according to the parameter.
getPattern() - Method in exception org.apache.commons.math.MathException
  Gets the pattern used to build the message of this throwable.
getPattern() - Method in exception org.apache.commons.math.MathRuntimeException
  Gets the pattern used to build the message of this throwable.
getPct(Object) - Method in class org.apache.commons.math.stat.Frequency
  Deprecated. replaced by `Frequency.getPct(Comparable)` as of 2.0
getPct(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPct(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPct(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPct(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPercentile(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns an estimate for the pth percentile of the stored values.
getPercentileImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured percentile implementation.
getPermutation() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the permutation associated with the lu decomposition.
getPhase() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Get the phase φ.
getPivot() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
  Returns the pivot permutation vector.
getPivot() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Returns the pivot permutation vector.
getPivot() - Method in interface org.apache.commons.math.linear.LUDecomposition
  Returns the pivot permutation vector.
getPivot() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
  Returns the pivot permutation vector.
getPivotColumn(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Returns the column with the most negative coefficient in the objective function row.
getPivotRow(SimplexTableau, int) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Returns the row with the minimum ratio as given by the minimum ratio test (MRT).
getPoint() - Method in class org.apache.commons.math.optimization.RealPointValuePair
  Get the point.
getPoint() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
  Get the point.
getPoint() - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
  Get the n-dimensional point in integer space.
getPointRef() - Method in class org.apache.commons.math.optimization.RealPointValuePair
  Get a reference to the point.
getPointRef() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
  Get a reference to the point.
getPoints() - Method in class org.apache.commons.math.stat.clustering.Cluster
  Get the points contained in the cluster.
getPolynomialFunction() - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Deprecated. as of 2.0 the function is not stored anymore within the instance.
getPolynomials() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Returns a copy of the interpolating polynomials array.
getPopulationLimit() - Method in class org.apache.commons.math.genetics.ListPopulation
  Access the maximum population size.
getPopulationLimit() - Method in interface org.apache.commons.math.genetics.Population
  Access the maximum population size.
getPopulationSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Access the population size.
getPopulationSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the population size.
getPopulationSize() - Method in class org.apache.commons.math.genetics.ListPopulation
  Access the current population size.
getPopulationSize() - Method in interface org.apache.commons.math.genetics.Population
  Access the current population size.
getPosition() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
  Returns the original position of the pair.
getPrefix() - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Get the format prefix.
getPrefix() - Method in class org.apache.commons.math.linear.RealVectorFormat
  Get the format prefix.
getPreviousTime() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Get the previous grid point time.
getPreviousTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Get the previous grid point time.
getPreviousTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Get the previous grid point time.
getPreviousTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Get the previous grid point time.
getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Access the probability of success for this distribution.
getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the probability of success for this distribution.
getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.PascalDistribution
  Access the probability of success for this distribution.
getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Access the probability of success for this distribution.
getProperInstance() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
  Returns the default complex format for the current locale.
getProperInstance(Locale) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
  Returns the default complex format for the given locale.
getProperInstance() - Static method in class org.apache.commons.math.fraction.FractionFormat
  Returns the default complex format for the current locale.
getProperInstance(Locale) - Static method in class org.apache.commons.math.fraction.FractionFormat
  Returns the default complex format for the given locale.
getPulsation() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Get the pulsation ω.
getQ() - Method in interface org.apache.commons.math.linear.QRDecomposition
  Returns the matrix Q of the decomposition.
getQ() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
  Returns the matrix Q of the decomposition.
getQ() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Returns the matrix Q of the transform.
getQ0() - Method in class org.apache.commons.math.geometry.Rotation
  Get the scalar coordinate of the quaternion.
getQ1() - Method in class org.apache.commons.math.geometry.Rotation
  Get the first coordinate of the vectorial part of the quaternion.
getQ2() - Method in class org.apache.commons.math.geometry.Rotation
  Get the second coordinate of the vectorial part of the quaternion.
getQ3() - Method in class org.apache.commons.math.geometry.Rotation
  Get the third coordinate of the vectorial part of the quaternion.
getQT() - Method in interface org.apache.commons.math.linear.QRDecomposition
  Returns the transpose of the matrix Q of the decomposition.
getQT() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
  Returns the transpose of the matrix Q of the decomposition.
getQT() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Returns the transpose of the matrix Q of the transform.
getQuantile() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
getR() - Method in interface org.apache.commons.math.linear.QRDecomposition
  Returns the matrix R of the decomposition.
getR() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
  Returns the matrix R of the decomposition.
getR() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns Pearson's product moment correlation coefficient, usually denoted r.
getRan() - Method in class org.apache.commons.math.random.RandomDataImpl
  Returns the RandomGenerator used to generate non-secure random data.
getRandomGenerator() - Static method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the (static) random generator.
getRank() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Return the effective numerical matrix rank.
getRank() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Return the effective numerical matrix rank.
getRank() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Get the rank of the covariance matrix.
getRankCorrelation() - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Returns a `PearsonsCorrelation` instance constructed from the ranked input data.
getReal() - Method in class org.apache.commons.math.complex.Complex
  Access the real part.
getRealEigenvalue(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns the real part of the ith eigenvalue of the original matrix.
getRealEigenvalue(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns the real part of the ith eigenvalue of the original matrix.
getRealEigenvalues() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns a copy of the real parts of the eigenvalues of the original matrix.
getRealEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns a copy of the real parts of the eigenvalues of the original matrix.
getRealFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
  Access the realFormat.
getReducedFraction(int, int) - Static method in class org.apache.commons.math.fraction.BigFraction
  Creates a `BigFraction` instance with the 2 parts of a fraction Y/Z.
getReducedFraction(int, int) - Static method in class org.apache.commons.math.fraction.Fraction
  Creates a `Fraction` instance with the 2 parts of a fraction Y/Z.
getRegressionSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared deviations of the predicted y values about their mean (which equals the mean of y).
getRegressionSumSquares(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Computes SSR from b1.
getRelationship() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
  Get the relationship between left and right hand sides.
getRelativeAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Get the actual relative accuracy.
getRelativeAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Get the actual relative accuracy.
getRelativeAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the actual relative accuracy.
getRepresentation() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
  Returns the (immutable) inner representation of the chromosome.
getResidual() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Get the residual for this measurement The residual is the measured value minus the theoretical value.
getResult() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
  Get the result of the last run of the integrator.
getResult() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Access the last computed integral.
getResult() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Get the result of the last run of the solver.
getResult() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Get the result of the last run of the solver.
getResult() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Get the result of the last run of the optimizer.
getResult() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Get the result of the last run of the optimizer.
getResult() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Get the result of the last run of the optimizer.
getResult() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Returns the value of the statistic based on the values that have been added.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Get the covariance matrix.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
  Get the mean vector.
getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Returns the current value of the Statistic.
getResult() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Returns the current value of the Statistic.
getResults(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array of the results of a statistic.
getRhsOffset() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the offset of the right hand side.
getRMS(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Get the Root Mean Square value.
getRMS(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
  Deprecated. Get the Root Mean Square value.
getRMS() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Get the Root Mean Square value.
getRootMatrix() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Get the root of the covariance matrix.
getRoundingMode() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Gets the rounding mode
getRoundingMode() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Gets the rounding mode for division operations The default is `BigDecimal.ROUND_HALF_UP`
getRoundingMode() - Method in class org.apache.commons.math.util.BigReal
  Gets the rounding mode for division operations The default is `RoundingMode.HALF_UP`
getRow(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entries in row number `row` as an array.
getRow(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entries in row number `row` as an array.
getRow(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in row number `row` as an array.
getRowAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entries in row number `row` as an array of double values.
getRowAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entries in row number `row` as an array of double values.
getRowDimension() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in interface org.apache.commons.math.linear.AnyMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Returns the number of rows in the matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in row number `row` as a row matrix.
getRowVector(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the entries in row number `row` as a vector.
getRowVector(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the entries in row number `row` as a vector.
getRowVector(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the entries in row number `row` as a vector.
getRowVector(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the entries in row number `row` as a vector.
getRowVector(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the entries in row number `row` as a vector.
getRowVector(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in row number `row` as a vector.
getRSquare() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the coefficient of determination, usually denoted r-square.
getS() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the diagonal matrix Σ of the decomposition.
getS() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the diagonal matrix Σ of the decomposition.
getSafety() - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Get the safety factor for stepsize control.
getSafety() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Get the safety factor for stepsize control.
getSampleSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Access the sample size.
getSampleSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the sample size.
getSampleStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns a `StatisticalSummary` describing this distribution.
getSampleStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns a `StatisticalSummary` describing this distribution.
getScale() - Method in interface org.apache.commons.math.distribution.CauchyDistribution
  Access the scale parameter.
getScale() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Access the scale parameter.
getScale() - Method in interface org.apache.commons.math.distribution.WeibullDistribution
  Access the scale parameter.
getScale() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Access the scale parameter.
getScale() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Sets the scale for division operations.
getScale() - Method in class org.apache.commons.math.util.BigReal
  Sets the scale for division operations.
getSecond() - Method in class org.apache.commons.math.genetics.ChromosomePair
  Access the second chromosome.
getSecondaryDiagonalRef() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Get the secondary diagonal elements of the matrix B of the transform.
getSecondaryDiagonalRef() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Get the secondary diagonal elements of the matrix T of the transform.
getSecondMoment() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns a statistic related to the Second Central Moment.
getSecondMoment() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns a statistic related to the Second Central Moment.
getSecRan() - Method in class org.apache.commons.math.random.RandomDataImpl
  Returns the SecureRandom used to generate secure random data.
getSelectionPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Returns the selection policy.
getSeparator() - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Get the format separator between components.
getSeparator() - Method in class org.apache.commons.math.linear.RealVectorFormat
  Get the format separator between components.
getShape() - Method in interface org.apache.commons.math.distribution.WeibullDistribution
  Access the shape parameter.
getShape() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Access the shape parameter.
getSigma() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property sigma.
getSignificance() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the significance level of the slope (equiv) correlation.
getSingularValues() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the diagonal elements of the matrix Σ of the decomposition.
getSingularValues() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the diagonal elements of the matrix Σ of the decomposition.
getSkewness() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the skewness of the available values.
getSkewnessImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured skewness implementation.
getSlackVariableOffset() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the offset of the first slack variable.
getSlope() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the slope of the estimated regression line.
getSlopeConfidenceInterval() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the half-width of a 95% confidence interval for the slope estimate.
getSlopeConfidenceInterval(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the half-width of a (100-100*alpha)% confidence interval for the slope estimate.
getSlopeStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the standard error of the slope estimate, usually denoted s(b1).
getSolution() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the current solution.
getSolver() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
  Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
  Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in interface org.apache.commons.math.linear.LUDecomposition
  Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
  Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in interface org.apache.commons.math.linear.QRDecomposition
  Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
  Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Get a solver for finding the A × X = B solution in least square sense.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Returns the solver absolute accuracy for inverse cum computation.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
getSortedValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the current set of values in an array of double primitives, sorted in ascending order.
getSparcity() - Method in class org.apache.commons.math.linear.OpenMapRealVector
getStandardDeviation() - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Access the standard deviation.
getStandardDeviation() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the standard deviation.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the standard deviation of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the standard deviation of the ith entries of the arrays that correspond to each multivariate sample
getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the standard deviation of the values that have been added.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the standard deviation of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the standard deviation of the values that have been added.
getStarterIntegrator() - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Get the starter integrator.
getStepHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Get all the step handlers that have been added to the integrator.
getStepHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Get all the step handlers that have been added to the integrator.
getStepHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Get all the step handlers that have been added to the integrator.
getStirlingError(double) - Static method in class org.apache.commons.math.distribution.SaddlePointExpansion
  Compute the error of Stirling's series at the given value.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Gets a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Gets a submatrix.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Gets a submatrix.
getSubVector(int, int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Get a subvector from consecutive elements.
getSubVector(int, int) - Method in interface org.apache.commons.math.linear.FieldVector
  Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Get a subvector from consecutive elements.
getSubVector(int, int) - Method in interface org.apache.commons.math.linear.RealVector
  Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Get a subvector from consecutive elements.
getSuffix() - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Get the format suffix.
getSuffix() - Method in class org.apache.commons.math.linear.RealVectorFormat
  Get the format suffix.
getSum() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the sum of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the sum of the ith entries of the arrays that correspond to each multivariate sample
getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getSum() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the sum of the values that have been added
getSum() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the sum of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getSum() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the sum of the values that have been added
getSumFreq() - Method in class org.apache.commons.math.stat.Frequency
  Returns the sum of all frequencies.
getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured sum implementation.
getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured Sum implementation
getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured Sum implementation
getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured Sum implementation
getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured Sum implementation
getSumLog() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getSumLog() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that correspond to each multivariate sample
getSumLog() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Returns the currently configured sum of logs implementation
getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured sum of logs implementation
getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured sum of logs implementation
getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured sum of logs implementation
getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured sum of logs implementation
getSummary() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Return a `StatisticalSummaryValues` instance reporting current aggregate statistics.
getSummary() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Return a `StatisticalSummaryValues` instance reporting current statistics.
getSummary() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Return a `StatisticalSummaryValues` instance reporting current statistics.
getSumOfCrossProducts() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of crossproducts, xi*yi.
getSumOfLogs() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the sum of the logs of all the aggregated data.
getSumOfLogs() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the sum of the logs of the values that have been added.
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the sum of the squares of all the aggregated data.
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the sum of the squares of the available values.
getSumSq() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getSumSq() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
  Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that correspond to each multivariate sample
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the sum of the squares of the values that have been added.
getSumSq() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that have been added using `MultivariateSummaryStatistics.addValue(double[])`
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the sum of the squares of the values that have been added.
getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured sum of squares implementation.
getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns the currently configured sum of squares implementation
getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured sum of squares implementation
getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns the currently configured sum of squares implementation
getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured sum of squares implementation
getSumSquaredErrors() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared errors (SSE) associated with the regression model.
getT() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Returns the tridiagonal matrix T of the transform.
getTheoreticalValue() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Get the theoretical value expected for this measurement
getTiesStrategy() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Return the TiesStrategy
getTotalSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared deviations of the y values about their mean.
getTrace() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTransformer(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
  Returns the Transformer that is mapped to a class if mapping is not present, this returns null.
getTTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Return a (singleton) TTest instance.
getU() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Returns the matrix U of the transform.
getU() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
  Returns the matrix U of the decomposition.
getU() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Returns the matrix U of the decomposition.
getU() - Method in interface org.apache.commons.math.linear.LUDecomposition
  Returns the matrix U of the decomposition.
getU() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
  Returns the matrix U of the decomposition.
getU() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the matrix U of the decomposition.
getU() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the matrix U of the decomposition.
getUnboundParameters() - Method in interface org.apache.commons.math.estimation.EstimationProblem
  Deprecated. Get the unbound parameters of the problem.
getUnboundParameters() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Get the unbound parameters of the problem.
getUnknownDistributionChiSquareTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Return a (singleton) UnknownDistributionChiSquareTest instance.
getUpperBounds() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns the array of upper bounds for the bins.
getUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns a fresh copy of the array of upper bounds for the bins.
getUpperDomain(int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Return the highest domain value for the given hypergeometric distribution parameters.
getUT() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the transpose of the matrix U of the decomposition.
getUT() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the transpose of the matrix U of the decomposition.
getV() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Returns the matrix V of the transform.
getV() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns the matrix V of the decomposition.
getV() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns the matrix V of the decomposition.
getV() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the matrix V of the decomposition.
getV() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the matrix V of the decomposition.
getValue() - Method in class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
  Get the value of the entry.
getValue() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
  Get the value of the entry.
getValue() - Method in class org.apache.commons.math.linear.RealVector.Entry
  Get the value of the entry.
getValue() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
  Get the value of the constraint (right hand side).
getValue(double[]) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Compute the value of the linear equation at the current point
getValue(RealVector) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Compute the value of the linear equation at the current point
getValue() - Method in class org.apache.commons.math.optimization.RealPointValuePair
  Get the value of the objective function.
getValue() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
  Get the value of the objective function.
getValue() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
  Returns the value of the pair.
getValueRef() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
  Get a reference to the value of the objective function.
getValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the current set of values in an array of double primitives.
getValues() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Returns the current set of values in an array of double primitives.
getValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Deprecated. replaced by `ResizableDoubleArray.getInternalValues()` as of 2.0
getValuesFileURL() - Method in class org.apache.commons.math.random.ValueServer
  Getter for `valuesFileURL```
getVariance() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Returns the variance of the available values.
getVariance() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the variance of the available values.
getVariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the variance of the available values.
getVariance() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getVariance() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the variance of the values that have been added.
getVariance() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the variance of the values that have been added.
getVarianceDirection() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns the varianceDirection property.
getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the currently configured variance implementation.
getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the currently configured variance implementation
getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns the currently configured variance implementation
getVT() - Method in interface org.apache.commons.math.linear.EigenDecomposition
  Returns the transpose of the matrix V of the decomposition.
getVT() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Returns the transpose of the matrix V of the decomposition.
getVT() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
  Returns the transpose of the matrix V of the decomposition.
getVT() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Returns the transpose of the matrix V of the decomposition.
getWeight() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Get the weight of the measurement in the least squares problem
getWeight() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Get the weight of the measurement in the fitting process.
getWholeFormat() - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
  Access the whole format.
getWholeFormat() - Method in class org.apache.commons.math.fraction.ProperFractionFormat
  Access the whole format.
getWidth() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the width of the tableau.
getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the maximum number of values that can be stored in the dataset, or INFINITE_WINDOW (-1) if there is no limit.
getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Returns the maximum number of values that can be stored in the dataset, or INFINITE_WINDOW (-1) if there is no limit.
getX() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the abscissa of the vector.
getX() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Get the abscissa of the point.
getXSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared deviations of the x values about their mean.
getY() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the ordinate of the vector.
getY() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Get the observed value of the function at x.
getZ() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the height of the vector.
getZero() - Method in class org.apache.commons.math.complex.ComplexField
  Get the additive identity of the field.
getZero() - Method in interface org.apache.commons.math.Field
  Get the additive identity of the field.
getZero() - Method in class org.apache.commons.math.fraction.BigFractionField
  Get the additive identity of the field.
getZero() - Method in class org.apache.commons.math.fraction.FractionField
  Get the additive identity of the field.
getZero() - Method in class org.apache.commons.math.util.BigRealField
  Get the additive identity of the field.
GillIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the Gill fourth order Runge-Kutta integrator for Ordinary Differential Equations .
GillIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Simple constructor.
GillStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a step interpolator for the Gill fourth order Runge-Kutta integrator.
GillStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Simple constructor.
GillStepInterpolator(GillStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Copy constructor.
GLSMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
  The GLS implementation of the multiple linear regression.
GLSMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
goal - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Type of optimization.
goal - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Type of optimization goal: either `GoalType.MAXIMIZE` or `GoalType.MINIMIZE`.
GoalType - Enum in org.apache.commons.math.optimization
  Goal type for an optimization problem.
GoalType() - Constructor for enum org.apache.commons.math.optimization.GoalType
GOLDEN_SECTION - Static variable in class org.apache.commons.math.optimization.univariate.BrentOptimizer
  Golden section.
gradient() - Method in interface org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction
  Returns the gradient function.
gradient(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter.ParametricHarmonicFunction
  Compute the gradient of the function with respect to its parameters.
gradient(double, double[]) - Method in interface org.apache.commons.math.optimization.fitting.ParametricRealFunction
  Compute the gradient of the function with respect to its parameters.
gradient(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter.ParametricPolynomial
  Compute the gradient of the function with respect to its parameters.
gradient - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Objective function gradient.
gradientEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Number of gradient evaluations.
GraggBulirschStoerIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a Gragg-Bulirsch-Stoer integrator for Ordinary Differential Equations.
GraggBulirschStoerIntegrator(double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Simple constructor.
GraggBulirschStoerIntegrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Simple constructor.
GraggBulirschStoerStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class implements an interpolator for the Gragg-Bulirsch-Stoer integrator.
GraggBulirschStoerStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Simple constructor.
GraggBulirschStoerStepInterpolator(double[], double[], double[], double[], double[][], boolean) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Simple constructor.
GraggBulirschStoerStepInterpolator(GraggBulirschStoerStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Copy constructor.
growTable() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Grow the tables.
growTable() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Grow the tables.
guess() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Estimate a first guess of the coefficients.
guessAOmega() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Estimate a first guess of the a and ω coefficients.
guessParametersErrors(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Guess the errors in unbound estimated parameters.
guessParametersErrors(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
  Deprecated. Guess the errors in estimated parameters.
guessParametersErrors() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Guess the errors in optimized parameters.
guessPhi() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Estimate a first guess of the φ coefficient.

## H

h - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  current time step
h - Variable in class org.apache.commons.math.ode.sampling.StepNormalizer
  Fixed time step.
HALF_LOG_2_PI - Static variable in class org.apache.commons.math.distribution.SaddlePointExpansion
  1/2 * log(2 π).
HALF_LOG_2_PI - Static variable in class org.apache.commons.math.special.Gamma
  Avoid repeated computation of log of 2 PI in logGamma
handler - Variable in class org.apache.commons.math.ode.events.EventState
  Event handler.
handler - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Underlying event handler with jacobians.
handler - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Underlying step handler with jacobians.
handler - Variable in class org.apache.commons.math.ode.sampling.StepNormalizer
  Underlying step handler.
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Handle the last accepted step.
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Handle the last accepted step
handleStep(StepInterpolatorWithJacobians, boolean) - Method in interface org.apache.commons.math.ode.jacobians.StepHandlerWithJacobians
  Handle the last accepted step
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
  Handle the last accepted step
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math.ode.sampling.DummyStepHandler
  Handle the last accepted step.
handleStep(double, double[], double[], boolean) - Method in interface org.apache.commons.math.ode.sampling.FixedStepHandler
  Handle the last accepted step
handleStep(StepInterpolator, boolean) - Method in interface org.apache.commons.math.ode.sampling.StepHandler
  Handle the last accepted step
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math.ode.sampling.StepNormalizer
  Handle the last accepted step
HarmonicCoefficientsGuesser - Class in org.apache.commons.math.optimization.fitting
  This class guesses harmonic coefficients from a sample.
HarmonicCoefficientsGuesser(WeightedObservedPoint[]) - Constructor for class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Simple constructor.
HarmonicFitter - Class in org.apache.commons.math.optimization.fitting
  This class implements a curve fitting specialized for sinusoids.
HarmonicFitter(DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.HarmonicFitter
  Simple constructor.
HarmonicFitter(DifferentiableMultivariateVectorialOptimizer, double[]) - Constructor for class org.apache.commons.math.optimization.fitting.HarmonicFitter
  Simple constructor.
HarmonicFitter.ParametricHarmonicFunction - Class in org.apache.commons.math.optimization.fitting
  Parametric harmonic function.
HarmonicFitter.ParametricHarmonicFunction() - Constructor for class org.apache.commons.math.optimization.fitting.HarmonicFitter.ParametricHarmonicFunction
HarmonicFunction - Class in org.apache.commons.math.optimization.fitting
  Harmonic function of the form `f (t) = a cos (ω t + φ)`.
HarmonicFunction(double, double, double) - Constructor for class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Simple constructor.
HasDensity<P> - Interface in org.apache.commons.math.distribution
  Deprecated. to be removed in math 3.0
hash(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns an integer hash code representing the given double value.
hash(double[]) - Static method in class org.apache.commons.math.util.MathUtils
  Returns an integer hash code representing the given double array.
hashCode() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
hashCode() - Method in class org.apache.commons.math.complex.Complex
  Get a hashCode for the complex number.
hashCode() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets a hashCode for the fraction.
hashCode() - Method in class org.apache.commons.math.fraction.Fraction
  Gets a hashCode for the fraction.
hashCode() - Method in class org.apache.commons.math.geometry.Vector3D
  Get a hashCode for the 3D vector.
hashCode() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Computes a hashcode for the matrix.
hashCode() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Computes a hashcode for the matrix.
hashCode() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Get a hashCode for the real vector.
hashCode() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Get a hashCode for the real vector.
hashCode() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Computes a hashcode for the matrix.
hashCode() - Method in class org.apache.commons.math.linear.OpenMapRealVector
hashCode() - Method in class org.apache.commons.math.linear.SparseFieldVector
hashCode() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
hashCode() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
hashCode() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
hashCode() - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
hashCode() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Returns hash code based on getResult() and getN()
hashCode() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
hashCode() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
hashCode() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.Frequency
hashCode() - Method in class org.apache.commons.math.util.BigReal
hashCode() - Method in class org.apache.commons.math.util.DefaultTransformer
hashCode() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns a hash code consistent with equals.
hashCode() - Method in class org.apache.commons.math.util.TransformerMap
hashOf(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Compute the hash value of a key
hashOf(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Compute the hash value of a key
hasNext() - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
hasNext() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
hasNext() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Check if there is a next element in the map.
hasNext() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Check if there is a next element in the map.
HERMITE_COEFFICIENTS - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Coefficients for Hermite polynomials.
HighamHall54Integrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the 5(4) Higham and Hall integrator for Ordinary Differential Equations.
HighamHall54Integrator(double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Simple constructor.
HighamHall54Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Simple constructor.
HighamHall54StepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class represents an interpolator over the last step during an ODE integration for the 5(4) Higham and Hall integrator.
HighamHall54StepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
  Simple constructor.
HighamHall54StepInterpolator(HighamHall54StepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
  Copy constructor.
homoscedasticT(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
homoscedasticT(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
homoscedasticT(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
homoscedasticT(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
homoscedasticT(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
homoscedasticT(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
homoscedasticT(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes t test statistic for 2-sample t-test under the hypothesis of equal subpopulation variances.
homoscedasticTTest(double[], double[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
homoscedasticTTest(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
homoscedasticTTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.
homoscedasticTTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, assuming that the subpopulation variances are equal.
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
homoscedasticTTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.
homoscedasticTTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, assuming that the subpopulation variances are equal.
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
homoscedasticTTest(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes p-value for 2-sided, 2-sample t-test, under the assumption of equal subpopulation variances.
householderVectors - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
  Householder vectors.
householderVectors - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
  Householder vectors.
hP - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Step sizes to use for computing the jacobian df/dp.
hY - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Step sizes to use for computing the jacobian df/dy.
HypergeometricDistribution - Interface in org.apache.commons.math.distribution
  The Hypergeometric Distribution.
HypergeometricDistributionImpl - Class in org.apache.commons.math.distribution
  The default implementation of `HypergeometricDistribution`.
HypergeometricDistributionImpl(int, int, int) - Constructor for class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Construct a new hypergeometric distribution with the given the population size, the number of successes in the population, and the sample size.

## I

I - Static variable in class org.apache.commons.math.complex.Complex
  The square root of -1.
IDENTITY - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The identity function.
IDENTITY - Static variable in class org.apache.commons.math.geometry.Rotation
  Identity rotation.
identityPermutation(int) - Static method in class org.apache.commons.math.genetics.RandomKey
  Generates a representation corresponding to an identity permutation of length l which can be passed to the RandomKey constructor.
ignored - Variable in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Ignore measurement indicator.
ILLEGAL_ACCESS_MESSAGE - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Message for illegal accesson setquantile.
illumination() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Get the illumination of the element.
imagEigenvalues - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Imaginary part of the realEigenvalues.
imagEigenvalues - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Imaginary part of the realEigenvalues.
imaginary - Variable in class org.apache.commons.math.complex.Complex
  The imaginary part.
imaginaryCharacter - Variable in class org.apache.commons.math.complex.ComplexFormat
  The notation used to signify the imaginary part of the complex number.
imaginaryFormat - Variable in class org.apache.commons.math.complex.ComplexFormat
  The format used for the imaginary part.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Mean
  Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  Boolean test to determine if this Variance should also increment the second moment, this evaluates to false when this Variance is constructed with an external SecondMoment as a parameter.
increasing - Variable in class org.apache.commons.math.ode.events.EventState
  Variation direction around pending event.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Add a new vector to the sample.
increment(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
  Add a new vector to the sample.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Updates the internal state of the statistic to reflect the addition of the new value.
incrementAll(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation just calls `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the input array.
incrementAll(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation just calls `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the specified portion of the input array.
incrementAll(double[]) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect addition of all values in the values array.
incrementAll(double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect addition of the values in the designated portion of the values array.
incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Increment the iterations counter by 1.
incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Increment the iterations counter by 1.
incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Increment the iterations counter by 1.
incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Increment the iterations counter by 1.
incrementJacobianEvaluationsCounter() - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Increment the jacobian evaluations counter.
index - Variable in class org.apache.commons.math.linear.RealVector.Entry
  Index of the entry.
index - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
  Current interpolator index.
indicator(byte) - Static method in class org.apache.commons.math.util.MathUtils
  For a byte value x, this method returns (byte)(+1) if x >= 0 and (byte)(-1) if x < 0.
indicator(double) - Static method in class org.apache.commons.math.util.MathUtils
  For a double precision value x, this method returns +1.0 if x >= 0 and -1.0 if x < 0.
indicator(float) - Static method in class org.apache.commons.math.util.MathUtils
  For a float value x, this method returns +1.0F if x >= 0 and -1.0F if x < 0.
indicator(int) - Static method in class org.apache.commons.math.util.MathUtils
  For an int value x, this method returns +1 if x >= 0 and -1 if x < 0.
indicator(long) - Static method in class org.apache.commons.math.util.MathUtils
  For a long value x, this method returns +1L if x >= 0 and -1L if x < 0.
indicator(short) - Static method in class org.apache.commons.math.util.MathUtils
  For a short value x, this method returns (short)(+1) if x >= 0 and (short)(-1) if x < 0.
inducedPermutation(List<S>, List<S>) - Static method in class org.apache.commons.math.genetics.RandomKey
  Generates a representation of a permutation corresponding to a permutation which yields `permutedData` when applied to `originalData`.
INF - Static variable in class org.apache.commons.math.complex.Complex
  A complex number representing "+INF + INFi"
INFINITE_WINDOW - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Represents an infinite window size.
initialCapacity - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The initial capacity of the array.
initialization - Variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Initialization matrix for the higher order derivatives wrt y'', y''' ...
initializeArrays() - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Initialize the integrator internal arrays.
initializeColumnLabels() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Initialize the labels for the columns.
initialized - Variable in class org.apache.commons.math.ode.events.CombinedEventsManager
  Initialization indicator.
initializeEstimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Initialization of the common parts of the estimation.
initializeHighOrderDerivatives(double[], double[][]) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(double[], double[][]) - Method in interface org.apache.commons.math.ode.MultistepIntegrator.NordsieckTransformer
  Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(double[], double[][]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(double[], double[][]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Initialize the high order scaled derivatives at step start.
initializeStep(FirstOrderDifferentialEquations, boolean, int, double[], double, double[], double[], double[], double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Initialize the integration step.
initialStep - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  User supplied initial step.
initialStep - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Initial step used to bracket the optimum in line search.
initialStepBoundFactor - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Positive input variable used in determining the initial step bound.
initialStepBoundFactor - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Positive input variable used in determining the initial step bound.
initialTime - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
  Initial integration time.
innerCumulativeProbability(int, int, int, int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
inputArray - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
  Array of input data values
inputStream - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
  Input stream providing access to the data
INSTANCE - Static variable in class org.apache.commons.math.complex.ComplexField.LazyHolder
  Cached field instance.
INSTANCE - Static variable in class org.apache.commons.math.fraction.BigFractionField.LazyHolder
  Cached field instance.
INSTANCE - Static variable in class org.apache.commons.math.fraction.FractionField.LazyHolder
  Cached field instance.
INSTANCE - Static variable in class org.apache.commons.math.ode.sampling.DummyStepHandler.LazyHolder
  Cached field instance.
INSTANCE - Static variable in class org.apache.commons.math.util.BigRealField.LazyHolder
  Cached field instance.
INSUFFICIENT_DATA_MESSAGE - Static variable in class org.apache.commons.math.stat.inference.TTestImpl
  Message for insufficient data.
IntegerDistribution - Interface in org.apache.commons.math.distribution
  Interface for discrete distributions of integer-valued random variables.
integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Deprecated.
integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Integrate the function in the given interval.
integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.RombergIntegrator
  Deprecated.
integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.RombergIntegrator
  Integrate the function in the given interval.
integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.SimpsonIntegrator
  Deprecated.
integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.SimpsonIntegrator
  Integrate the function in the given interval.
integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Deprecated.
integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Integrate the function in the given interval.
integrate(double, double) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
  Deprecated. replaced by `UnivariateRealIntegrator.integrate(UnivariateRealFunction, double, double)` since 2.0
integrate(UnivariateRealFunction, double, double) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
  Integrate the function in the given interval.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in interface org.apache.commons.math.ode.FirstOrderIntegrator
  Integrate the differential equations up to the given time.
integrate(double, double[], double[][], double, double[], double[][], double[][]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Integrate the differential equations and the variational equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
  Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
  Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Integrate the differential equations up to the given time.
integrate(SecondOrderDifferentialEquations, double, double[], double[], double, double[], double[]) - Method in interface org.apache.commons.math.ode.SecondOrderIntegrator
  Integrate the differential equations up to the given time
integrator - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Underlying integrator for compound problem.
integrator - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
  Reference to the integrator.
IntegratorException - Exception in org.apache.commons.math.ode
  This exception is made available to users to report the error conditions that are triggered during integration
IntegratorException(String, Object...) - Constructor for exception org.apache.commons.math.ode.IntegratorException
  Simple constructor.
IntegratorException(Throwable) - Constructor for exception org.apache.commons.math.ode.IntegratorException
  Create an exception with a given root cause.
internalArray - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The internal storage array.
interpolate(double[], double[], double[][]) - Method in interface org.apache.commons.math.analysis.interpolation.BivariateRealGridInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a `SplineInterpolator` on the resulting fit.
interpolate(double[][], double[]) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Computes an interpolating function for the data set.
interpolate(double[][], double[]) - Method in interface org.apache.commons.math.analysis.interpolation.MultivariateRealInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.NevilleInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[], double[][]) - Method in class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.SplineInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in interface org.apache.commons.math.analysis.interpolation.UnivariateRealInterpolator
  Computes an interpolating function for the data set.
interpolatedDerivatives - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  interpolated derivatives
interpolatedState - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  interpolated state
interpolatedTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  interpolated time
interpolator - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Wrapped interpolator.
intValue() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as an `int`.
intValue() - Method in class org.apache.commons.math.fraction.Fraction
  Gets the fraction as an `int`.
InvalidMatrixException - Exception in org.apache.commons.math.linear
  Thrown when a system attempts an operation on a matrix, and that matrix does not satisfy the preconditions for the aforementioned operation.
InvalidMatrixException(String, Object...) - Constructor for exception org.apache.commons.math.linear.InvalidMatrixException
  Construct an exception with the given message.
InvalidMatrixException(Throwable) - Constructor for exception org.apache.commons.math.linear.InvalidMatrixException
  Construct an exception with the given message.
InvalidRepresentationException - Exception in org.apache.commons.math.genetics
  Exception indicating that the representation of a chromosome is not valid.
InvalidRepresentationException() - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
  Constructor
InvalidRepresentationException(String) - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
  Construct an InvalidRepresentationException
InvalidRepresentationException(Throwable) - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
  Construct an InvalidRepresentationException
InvalidRepresentationException(String, Throwable) - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
  Construct an InvalidRepresentationException
inverse() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated.
inverse() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the inverse of this matrix.
inverse() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the inverse matrix if this matrix is invertible.
inverse() - Method in interface org.apache.commons.math.linear.RealMatrix
  Deprecated. as of release 2.0, replaced by ``new LUDecompositionImpl(m)`.`getSolver()`.`getInverse()``
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤ `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  For this distribution, X, this method returns the largest x, such that P(X ≤ x) ≤ `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.ContinuousDistribution
  For this distribution, X, this method returns x such that P(X < x) = p.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For this distribution, X, this method returns the largest x such that P(X ≤ x) <= p.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  For this distribution, X, this method returns the largest x, such that P(X ≤ x) ≤ `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Inversely transform the given real data set.
inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Inversely transform the given real data set.
inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Inversely transform the given complex data set.
inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  Inversely transform the given real data set.
inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Inversely transform the given real data set.
inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform(double[]) - Method in interface org.apache.commons.math.transform.RealTransformer
  Inversely transform the given real data set.
inversetransform(UnivariateRealFunction, double, double, int) - Method in interface org.apache.commons.math.transform.RealTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform2(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Inversely transform the given real data set.
inversetransform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform2(double[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Inversely transform the given real data set.
inversetransform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Inversely transform the given real function, sampled on the given interval.
inversetransform2(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Inversely transform the given complex data set.
inversetransform2(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Inversely transform the given real data set.
inversetransform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Inversely transform the given real function, sampled on the given interval.
INVERT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The invert operator wrapped as a `ComposableFunction`.
isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Returns true iff biasCorrected property is set to true.
isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
isBiasCorrected - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  Determines whether or not bias correction is applied when computing the value of the statisic.
isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
isBiasCorrected - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Indicator for bias correction.
isBound() - Method in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Check if the parameter is bound
isBracketing(double, double, UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Returns true iff the function takes opposite signs at the endpoints.
isDefaultValue(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Determine if this value is within epsilon of zero.
isEmpty() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Check if the manager does not manage any event handlers.
isForward() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Check if the natural integration direction is forward.
isForward() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Check if the natural integration direction is forward.
isForward() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Check if the natural integration direction is forward.
isForward() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Check if the natural integration direction is forward.
isForward - Variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Forward/reverse indicator.
isForward() - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Check if computation has been done for forward or reverse transform.
isIgnored() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Check if this measurement should be ignored
isInfinite - Variable in class org.apache.commons.math.complex.Complex
  Record whether this complex number is infinite.
isInfinite() - Method in class org.apache.commons.math.complex.Complex
  Returns true if either the real or imaginary part of this complex number takes an infinite value (either `Double.POSITIVE_INFINITY` or `Double.NEGATIVE_INFINITY`) and neither part is `NaN`.
isInfinite() - Method in class org.apache.commons.math.geometry.Vector3D
  Returns true if any coordinate of this vector is infinite and none are NaN; false otherwise
isInfinite() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns true if any coordinate of this vector is infinite and none are NaN; false otherwise
isInfinite() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Returns true if any coordinate of this vector is infinite and none are NaN; false otherwise
isInfinite() - Method in interface org.apache.commons.math.linear.RealVector
  Returns true if any coordinate of this vector is infinite and none are NaN; false otherwise
isLoaded() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Property indicating whether or not the distribution has been loaded.
isLoaded() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Property indicating whether or not the distribution has been loaded.
isNaN - Variable in class org.apache.commons.math.complex.Complex
  Record whether this complex number is equal to NaN.
isNaN() - Method in class org.apache.commons.math.complex.Complex
  Returns true if either or both parts of this complex number is NaN; false otherwise
isNaN() - Method in class org.apache.commons.math.geometry.Vector3D
  Returns true if any coordinate of this vector is NaN; false otherwise
isNaN() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Returns true if any coordinate of this vector is NaN; false otherwise
isNaN() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Returns true if any coordinate of this vector is NaN; false otherwise
isNaN() - Method in interface org.apache.commons.math.linear.RealVector
  Returns true if any coordinate of this vector is NaN; false otherwise
isNonSingular() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in interface org.apache.commons.math.linear.DecompositionSolver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Check if the decomposed matrix is non-singular.
isNonSingular() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Check if the decomposed matrix is non-singular.
isOptimal() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Returns whether the problem is at an optimal state.
isPowerOf2(long) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Returns true if the argument is power of 2.
isRootOK(double, double, Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Returns true iff the given complex root is actually a real zero in the given interval, within the solver tolerance level.
isSame(Chromosome) - Method in class org.apache.commons.math.genetics.BinaryChromosome
  Returns `true`iff `another` has the same representation and therefore the same fitness.``
isSame(Chromosome) - Method in class org.apache.commons.math.genetics.Chromosome
  Returns `true`iff `another` has the same representation and therefore the same fitness.``
isSame(Chromosome) - Method in class org.apache.commons.math.genetics.RandomKey
  Returns `true` iff `another` is a RandomKey and encodes the same permutation.
isSatisfied(Population) - Method in class org.apache.commons.math.genetics.FixedGenerationCount
  Determine whether or not the given number of generations have passed.
isSatisfied(Population) - Method in interface org.apache.commons.math.genetics.StoppingCondition
  Determine whether or not the given population satisfies the stopping condition.
isSequence(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Returns true if the arguments form a (strictly) increasing sequence
isSingular() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated.
isSingular() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Is this a singular matrix?
isSingular() - Method in interface org.apache.commons.math.linear.RealMatrix
  Deprecated. as of release 2.0, replaced by the boolean negation of ``new LUDecompositionImpl(m)`.`getSolver()`.`isNonSingular()``
isSquare() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Is this a square matrix?
isSquare() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Is this a square matrix?
isSquare() - Method in interface org.apache.commons.math.linear.AnyMatrix
  Is this a square matrix?
isSquare() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Is this a square matrix?
isStrictlyIncreasing(double[]) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Determines if the given array is ordered in a strictly increasing fashion.
isSymmetric(RealMatrix) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Check if a matrix is symmetric.
isUpperBiDiagonal() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Check if the matrix is transformed to upper bi-diagonal.
iter - Variable in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
  Iterator pointing to the entry.
iter - Variable in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
  Underlying iterator.
iterateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Compute the next simplex of the algorithm.
iterateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.MultiDirectional
  Compute the next simplex of the algorithm.
iterateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.NelderMead
  Compute the next simplex of the algorithm.
iterationCount - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  The last iteration count.
iterations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Number of iterations already performed.
iterations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Number of iterations already performed.
iterations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Number of iterations already performed.
iterations - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Number of iterations already performed.
iterator() - Method in class org.apache.commons.math.genetics.ListPopulation
  Chromosome list iterator
iterator() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Generic dense iterator - starts with index == zero, and hasNext() == true until index == getDimension();
iterator() - Method in interface org.apache.commons.math.linear.RealVector
  Generic dense iterator - starts with index == zero, and hasNext() == true until index == getDimension();
iterator() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Get an iterator over map elements.
iterator() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Get an iterator over map elements.

## J

jacNorm - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Norms of the columns of the jacobian matrix.
jacNorm - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Norms of the columns of the jacobian matrix.
jacobian() - Method in interface org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction
  Returns the jacobian function.
jacobian - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Jacobian matrix.
jacobian() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter.TheoreticalValuesFunction
  Returns the jacobian function.
jacobian - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Jacobian matrix.
jacobianEvaluations - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Number of jacobian evaluations.
jacobianEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Number of jacobian evaluations.
JDKRandomGenerator - Class in org.apache.commons.math.random
  Extension of `java.util.Random` to implement `RandomGenerator`.
JDKRandomGenerator() - Constructor for class org.apache.commons.math.random.JDKRandomGenerator
jF - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Objective function derivatives.

## K

k - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Number of parameters.
k - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Dimension of the data.
K14_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 1.
K14_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 6.
K14_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 7.
K14_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 8.
K14_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 9.
K14_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 10.
K14_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 11.
K14_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 12.
K14_13 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 14, element 13.
K15_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 1.
K15_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 6.
K15_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 7.
K15_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 8.
K15_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 9.
K15_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 10.
K15_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 11.
K15_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 12.
K15_13 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 13.
K15_14 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 15, element 14.
K16_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 1.
K16_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 6.
K16_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 7.
K16_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 8.
K16_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 9.
K16_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 10.
K16_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 11.
K16_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 12.
K16_13 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 13.
K16_14 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 14.
K16_15 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Internal weights for stage 16, element 15.
key() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Get the key of current entry.
key() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Get the key of current entry.
keys - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Keys table.
keys - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Keys table.
khi - Variable in class org.apache.commons.math.optimization.direct.MultiDirectional
  Expansion coefficient.
khi - Variable in class org.apache.commons.math.optimization.direct.NelderMead
  Expansion coefficient.
KMeansPlusPlusClusterer<T extends Clusterable<T>> - Class in org.apache.commons.math.stat.clustering
  Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.
KMeansPlusPlusClusterer(Random) - Constructor for class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
  Build a clusterer.
knots - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Spline segment interval delimiters (knots).
Kurtosis - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the Kurtosis of the available values.
Kurtosis() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Construct a Kurtosis
Kurtosis(FourthMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Construct a Kurtosis from an external moment
Kurtosis(Kurtosis) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Copy constructor, creates a new `Kurtosis` identical to the `original`
kurtosisImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Kurtosis statistic implementation - can be reset by setter.

## L

LAGUERRE_COEFFICIENTS - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Coefficients for Laguerre polynomials.
LaguerreSolver - Class in org.apache.commons.math.analysis.solvers
  Implements the Laguerre's Method for root finding of real coefficient polynomials.
LaguerreSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `LaguerreSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
LaguerreSolver() - Constructor for class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Construct a solver.
LANCZOS - Static variable in class org.apache.commons.math.special.Gamma
  Lanczos coefficients
lastDerivatives - Variable in class org.apache.commons.math.ode.sampling.StepNormalizer
  Last Derivatives vector.
lastState - Variable in class org.apache.commons.math.ode.sampling.StepNormalizer
  Last State vector.
lastTime - Variable in class org.apache.commons.math.ode.sampling.StepNormalizer
  Last step time.
lcm(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the least common multiple of the absolute value of two numbers, using the formula `lcm(a,b) = (a / gcd(a,b)) * b`.
lcm(long, long) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the least common multiple of the absolute value of two numbers, using the formula `lcm(a,b) = (a / gcd(a,b)) * b`.
LeastSquaresConverter - Class in org.apache.commons.math.optimization
  This class converts `vectorial objective functions` to `scalar objective functions` when the goal is to minimize them.
LeastSquaresConverter(MultivariateVectorialFunction, double[]) - Constructor for class org.apache.commons.math.optimization.LeastSquaresConverter
  Build a simple converter for uncorrelated residuals with the same weight.
LeastSquaresConverter(MultivariateVectorialFunction, double[], double[]) - Constructor for class org.apache.commons.math.optimization.LeastSquaresConverter
  Build a simple converter for uncorrelated residuals with the specific weights.
LeastSquaresConverter(MultivariateVectorialFunction, double[], RealMatrix) - Constructor for class org.apache.commons.math.optimization.LeastSquaresConverter
  Build a simple converter for correlated residuals with the specific weights.
LEGENDRE_COEFFICIENTS - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Coefficients for Legendre polynomials.
LegendreGaussIntegrator - Class in org.apache.commons.math.analysis.integration
  Implements the Legendre-Gauss quadrature formula.
LegendreGaussIntegrator(int, int) - Constructor for class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Build a Legendre-Gauss integrator.
LevenbergMarquardtEstimator - Class in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
LevenbergMarquardtEstimator() - Constructor for class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Build an estimator for least squares problems.
LevenbergMarquardtOptimizer - Class in org.apache.commons.math.optimization.general
  This class solves a least squares problem using the Levenberg-Marquardt algorithm.
LevenbergMarquardtOptimizer() - Constructor for class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Build an optimizer for least squares problems.
LinearConstraint - Class in org.apache.commons.math.optimization.linear
  A linear constraint for a linear optimization problem.
LinearConstraint(double[], Relationship, double) - Constructor for class org.apache.commons.math.optimization.linear.LinearConstraint
  Build a constraint involving a single linear equation.
LinearConstraint(RealVector, Relationship, double) - Constructor for class org.apache.commons.math.optimization.linear.LinearConstraint
  Build a constraint involving a single linear equation.
LinearConstraint(double[], double, Relationship, double[], double) - Constructor for class org.apache.commons.math.optimization.linear.LinearConstraint
  Build a constraint involving two linear equations.
LinearConstraint(RealVector, double, Relationship, RealVector, double) - Constructor for class org.apache.commons.math.optimization.linear.LinearConstraint
  Build a constraint involving two linear equations.
linearConstraints - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Linear constraints.
LinearObjectiveFunction - Class in org.apache.commons.math.optimization.linear
  An objective function for a linear optimization problem.
LinearObjectiveFunction(double[], double) - Constructor for class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
LinearObjectiveFunction(RealVector, double) - Constructor for class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
LinearOptimizer - Interface in org.apache.commons.math.optimization.linear
  This interface represents an optimization algorithm for linear problems.
ListPopulation - Class in org.apache.commons.math.genetics
  Population of chromosomes represented by a `List`.
ListPopulation(List<Chromosome>, int) - Constructor for class org.apache.commons.math.genetics.ListPopulation
  Creates a new ListPopulation instance.
ListPopulation(int) - Constructor for class org.apache.commons.math.genetics.ListPopulation
  Creates a new ListPopulation instance and initializes its inner chromosome list.
lmDir - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Parameters evolution direction associated with lmPar.
lmDir - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Parameters evolution direction associated with lmPar.
lmPar - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Levenberg-Marquardt parameter.
lmPar - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Levenberg-Marquardt parameter.
load(double[]) - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Computes the empirical distribution from the provided array of numbers.
load(File) - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Computes the empirical distribution from the input file.
load(URL) - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Computes the empirical distribution using data read from a URL.
load(double[]) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Computes the empirical distribution from the provided array of numbers.
load(URL) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Computes the empirical distribution using data read from a URL.
load(File) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Computes the empirical distribution from the input file.
LOAD_FACTOR - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Load factor for the map.
LOAD_FACTOR - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Load factor for the map.
loaded - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  is the distribution loaded?
localMin(UnivariateRealFunction, GoalType, double, double, double, double) - Method in class org.apache.commons.math.optimization.univariate.BrentOptimizer
  Find the minimum of the function `f` within the interval `(a, b)`.
locatePoint(double, StepInterpolator) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Compare a step interval and a double.
LoessInterpolator - Class in org.apache.commons.math.analysis.interpolation
  Implements the Local Regression Algorithm (also Loess, Lowess) for interpolation of real univariate functions.
LoessInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Constructs a new `LoessInterpolator` with a bandwidth of `LoessInterpolator.DEFAULT_BANDWIDTH`, `LoessInterpolator.DEFAULT_ROBUSTNESS_ITERS` robustness iterations and an accuracy of {#link #DEFAULT_ACCURACY}.
LoessInterpolator(double, int) - Constructor for class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Constructs a new `LoessInterpolator` with given bandwidth and number of robustness iterations.
LoessInterpolator(double, int, double) - Constructor for class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Constructs a new `LoessInterpolator` with given bandwidth, number of robustness iterations and accuracy.
LOG - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.log` method wrapped as a `ComposableFunction`.
log() - Method in class org.apache.commons.math.complex.Complex
  Compute the natural logarithm of this complex number.
log(double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the logarithm for base `b` of `x`.
LOG10 - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.log10` method wrapped as a `ComposableFunction`.
LOG1P - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.log1p` method wrapped as a `ComposableFunction`.
logBeta(double, double) - Static method in class org.apache.commons.math.special.Beta
  Returns the natural logarithm of the beta function B(a, b).
logBeta(double, double, double, int) - Static method in class org.apache.commons.math.special.Beta
  Returns the natural logarithm of the beta function B(a, b).
logBinomialProbability(int, int, double, double) - Static method in class org.apache.commons.math.distribution.SaddlePointExpansion
  Compute the PMF for a binomial distribution using the saddle point expansion.
logGamma(double) - Static method in class org.apache.commons.math.special.Gamma
  Returns the natural logarithm of the gamma function Γ(x).
longValue() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction as a `long`.
longValue() - Method in class org.apache.commons.math.fraction.Fraction
  Gets the fraction as a `long`.
lTData - Variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
  Row-oriented storage for LT matrix data.
lTData - Variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Row-oriented storage for LT matrix data.
lu - Variable in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated. as of release 2.0, since all methods using this are deprecated
lu - Variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Entries of cached LU decomposition.
lu - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Entries of LU decomposition.
lu - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Entries of LU decomposition.
lu - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Entries of LU decomposition.
lu - Variable in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Entries of LU decomposition.
luDecompose() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated. as of release 2.0, replaced by `LUDecomposition`
luDecompose() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Computes a new LU decompostion for this matrix, storing the result for use by other methods.
LUDecomposition - Interface in org.apache.commons.math.linear
  An interface to classes that implement an algorithm to calculate the LU-decomposition of a real matrix.
LUDecompositionImpl - Class in org.apache.commons.math.linear
  Calculates the LUP-decomposition of a square matrix.
LUDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.LUDecompositionImpl
  Calculates the LU-decomposition of the given matrix.
LUDecompositionImpl(RealMatrix, double) - Constructor for class org.apache.commons.math.linear.LUDecompositionImpl
  Calculates the LU-decomposition of the given matrix.
LUDecompositionImpl.Solver - Class in org.apache.commons.math.linear
  Specialized solver.
LUDecompositionImpl.Solver(double[][], int[], boolean) - Constructor for class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Build a solver from decomposed matrix.

## M

m - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Number of rows of the initial matrix.
M - Static variable in class org.apache.commons.math.random.MersenneTwister
  Period second parameter.
m1 - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  First moment of values that have been added
m2 - Variable in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  second moment of values that have been added
m3 - Variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  third moment of values that have been added
m4 - Variable in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  fourth moment of values that have been added
MAG01 - Static variable in class org.apache.commons.math.random.MersenneTwister
  X * MATRIX_A for X = {0, 1}.
main - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
  Main diagonal.
main - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Main diagonal of the tridiagonal matrix.
main - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
  Main diagonal.
map(UnivariateRealFunction) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Acts as if implemented as: return copy().map(function);
map(UnivariateRealFunction) - Method in interface org.apache.commons.math.linear.RealVector
  Acts as if implemented as: return copy().map(function);
map - Variable in class org.apache.commons.math.util.TransformerMap
  The internal Map.
mapAbs() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.abs(double)` function to each entry.
mapAbs() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.abs(double)` function to each entry.
mapAbsToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.abs(double)` function to each entry.
mapAbsToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.abs(double)` function to each entry.
mapAbsToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.abs(double)` function to each entry.
mapAcos() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.acos(double)` function to each entry.
mapAcos() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.acos(double)` function to each entry.
mapAcosToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.acos(double)` function to each entry.
mapAcosToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.acos(double)` function to each entry.
mapAcosToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.acos(double)` function to each entry.
mapAdd(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map an addition operation to each entry.
mapAdd(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map an addition operation to each entry.
mapAdd(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map an addition operation to each entry.
mapAdd(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Map an addition operation to each entry.
mapAdd(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map an addition operation to each entry.
mapAdd(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map an addition operation to each entry.
mapAddToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map an addition operation to each entry.
mapAddToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map an addition operation to each entry.
mapAddToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map an addition operation to each entry.
mapAddToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map an addition operation to each entry.
mapAddToSelf(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Map an addition operation to each entry.
mapAddToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map an addition operation to each entry.
mapAddToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map an addition operation to each entry.
mapAsin() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.asin(double)` function to each entry.
mapAsin() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.asin(double)` function to each entry.
mapAsinToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.asin(double)` function to each entry.
mapAsinToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.asin(double)` function to each entry.
mapAsinToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.asin(double)` function to each entry.
mapAtan() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.atan(double)` function to each entry.
mapAtan() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.atan(double)` function to each entry.
mapAtanToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.atan(double)` function to each entry.
mapAtanToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.atan(double)` function to each entry.
mapAtanToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.atan(double)` function to each entry.
mapCbrt() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCbrt() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCbrtToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCbrtToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCbrtToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCeil() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.ceil(double)` function to each entry.
mapCeil() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.ceil(double)` function to each entry.
mapCeilToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.ceil(double)` function to each entry.
mapCeilToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.ceil(double)` function to each entry.
mapCeilToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.ceil(double)` function to each entry.
mapCos() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.cos(double)` function to each entry.
mapCos() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.cos(double)` function to each entry.
mapCosh() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.cosh(double)` function to each entry.
mapCosh() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.cosh(double)` function to each entry.
mapCoshToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.cosh(double)` function to each entry.
mapCoshToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.cosh(double)` function to each entry.
mapCoshToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.cosh(double)` function to each entry.
mapCosToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.cos(double)` function to each entry.
mapCosToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.cos(double)` function to each entry.
mapCosToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.cos(double)` function to each entry.
mapDivide(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a division operation to each entry.
mapDivide(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a division operation to each entry.
mapDivide(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map a division operation to each entry.
mapDivide(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a division operation to each entry.
mapDivide(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map a division operation to each entry.
mapDivideToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a division operation to each entry.
mapDivideToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a division operation to each entry.
mapDivideToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map a division operation to each entry.
mapDivideToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map a division operation to each entry.
mapDivideToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a division operation to each entry.
mapDivideToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map a division operation to each entry.
mapExp() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.exp(double)` function to each entry.
mapExp() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.exp(double)` function to each entry.
mapExpm1() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpm1() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpm1ToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpm1ToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpm1ToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.exp(double)` function to each entry.
mapExpToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.exp(double)` function to each entry.
mapExpToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.exp(double)` function to each entry.
mapFloor() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.floor(double)` function to each entry.
mapFloor() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.floor(double)` function to each entry.
mapFloorToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.floor(double)` function to each entry.
mapFloorToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.floor(double)` function to each entry.
mapFloorToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.floor(double)` function to each entry.
mapInv() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the 1/x function to each entry.
mapInv() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map the 1/x function to each entry.
mapInv() - Method in interface org.apache.commons.math.linear.FieldVector
  Map the 1/x function to each entry.
mapInv() - Method in interface org.apache.commons.math.linear.RealVector
  Map the 1/x function to each entry.
mapInv() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map the 1/x function to each entry.
mapInvToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the 1/x function to each entry.
mapInvToSelf() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map the 1/x function to each entry.
mapInvToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the 1/x function to each entry.
mapInvToSelf() - Method in interface org.apache.commons.math.linear.FieldVector
  Map the 1/x function to each entry.
mapInvToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the 1/x function to each entry.
mapInvToSelf() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map the 1/x function to each entry.
mapLog() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.log(double)` function to each entry.
mapLog() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.log(double)` function to each entry.
mapLog10() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.log10(double)` function to each entry.
mapLog10() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.log10(double)` function to each entry.
mapLog10ToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.log10(double)` function to each entry.
mapLog10ToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.log10(double)` function to each entry.
mapLog10ToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.log10(double)` function to each entry.
mapLog1p() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.log1p(double)` function to each entry.
mapLog1p() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.log1p(double)` function to each entry.
mapLog1pToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.log1p(double)` function to each entry.
mapLog1pToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.log1p(double)` function to each entry.
mapLog1pToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.log1p(double)` function to each entry.
mapLogToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.log(double)` function to each entry.
mapLogToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.log(double)` function to each entry.
mapLogToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.log(double)` function to each entry.
mapMultiply(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a multiplication operation to each entry.
mapMultiply(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a multiplication operation to each entry.
mapMultiply(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map a multiplication operation to each entry.
mapMultiply(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a multiplication operation to each entry.
mapMultiply(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map a multiplication operation to each entry.
mapMultiplyToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a multiplication operation to each entry.
mapMultiplyToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a multiplication operation to each entry.
mapMultiplyToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map a multiplication operation to each entry.
mapMultiplyToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map a multiplication operation to each entry.
mapMultiplyToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a multiplication operation to each entry.
mapMultiplyToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map a multiplication operation to each entry.
mapPow(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a power operation to each entry.
mapPow(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a power operation to each entry.
mapPowToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a power operation to each entry.
mapPowToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map a power operation to each entry.
mapPowToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a power operation to each entry.
mapRint() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.rint(double)` function to each entry.
mapRint() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.rint(double)` function to each entry.
mapRintToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.rint(double)` function to each entry.
mapRintToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.rint(double)` function to each entry.
mapRintToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.rint(double)` function to each entry.
mapSignum() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.signum(double)` function to each entry.
mapSignum() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.signum(double)` function to each entry.
mapSignumToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.signum(double)` function to each entry.
mapSignumToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.signum(double)` function to each entry.
mapSignumToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.signum(double)` function to each entry.
mapSin() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.sin(double)` function to each entry.
mapSin() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.sin(double)` function to each entry.
mapSinh() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinh() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinhToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinhToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinhToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.sin(double)` function to each entry.
mapSinToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.sin(double)` function to each entry.
mapSinToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.sin(double)` function to each entry.
mapSqrt() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSqrt() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSqrtToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSqrtToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSqrtToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSubtract(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a subtraction operation to each entry.
mapSubtract(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a subtraction operation to each entry.
mapSubtract(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map a subtraction operation to each entry.
mapSubtract(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a subtraction operation to each entry.
mapSubtract(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map a subtraction operation to each entry.
mapSubtractToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map a subtraction operation to each entry.
mapSubtractToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a subtraction operation to each entry.
mapSubtractToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map a subtraction operation to each entry.
mapSubtractToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Map a subtraction operation to each entry.
mapSubtractToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
  Map a subtraction operation to each entry.
mapSubtractToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Map a subtraction operation to each entry.
mapTan() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.tan(double)` function to each entry.
mapTan() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.tan(double)` function to each entry.
mapTanh() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanh() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanhToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanhToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanhToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.tan(double)` function to each entry.
mapTanToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.tan(double)` function to each entry.
mapTanToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.tan(double)` function to each entry.
mapToSelf(UnivariateRealFunction) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Acts as if it is implemented as: Entry e = null; for(Iterator<Entry> it = iterator(); it.hasNext(); e = it.next()) { e.setValue(function.value(e.getValue())); }
mapToSelf(UnivariateRealFunction) - Method in interface org.apache.commons.math.linear.RealVector
  Acts as if it is implemented as: Entry e = null; for(Iterator<Entry> it = iterator(); it.hasNext(); e = it.next()) { e.setValue(function.value(e.getValue())); }
mapUlp() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.ulp(double)` function to each entry.
mapUlp() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.ulp(double)` function to each entry.
mapUlpToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Map the `Math.ulp(double)` function to each entry.
mapUlpToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.ulp(double)` function to each entry.
mapUlpToSelf() - Method in interface org.apache.commons.math.linear.RealVector
  Map the `Math.ulp(double)` function to each entry.
mask - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Bit mask for hash values.
mask - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Bit mask for hash values.
MathConfigurationException - Exception in org.apache.commons.math
  Signals a configuration problem with any of the factory methods.
MathConfigurationException() - Constructor for exception org.apache.commons.math.MathConfigurationException
  Default constructor.
MathConfigurationException(String, Object...) - Constructor for exception org.apache.commons.math.MathConfigurationException
  Constructs an exception with specified formatted detail message.
MathConfigurationException(Throwable) - Constructor for exception org.apache.commons.math.MathConfigurationException
  Create an exception with a given root cause.
MathConfigurationException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.MathConfigurationException
  Constructs an exception with specified formatted detail message and root cause.
MathException - Exception in org.apache.commons.math
  Base class for commons-math checked exceptions.
MathException() - Constructor for exception org.apache.commons.math.MathException
  Constructs a new `MathException` with no detail message.
MathException(String, Object...) - Constructor for exception org.apache.commons.math.MathException
  Constructs a new `MathException` with specified formatted detail message.
MathException(Throwable) - Constructor for exception org.apache.commons.math.MathException
  Constructs a new `MathException` with specified nested `Throwable` root cause.
MathException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.MathException
  Constructs a new `MathException` with specified formatted detail message and nested `Throwable` root cause.
MathRuntimeException - Exception in org.apache.commons.math
  Base class for commons-math unchecked exceptions.
MathRuntimeException(String, Object...) - Constructor for exception org.apache.commons.math.MathRuntimeException
  Constructs a new `MathRuntimeException` with specified formatted detail message.
MathRuntimeException(Throwable) - Constructor for exception org.apache.commons.math.MathRuntimeException
  Constructs a new `MathRuntimeException` with specified nested `Throwable` root cause.
MathRuntimeException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.MathRuntimeException
  Constructs a new `MathRuntimeException` with specified formatted detail message and nested `Throwable` root cause.
MathUtils - Class in org.apache.commons.math.util
  Some useful additions to the built-in functions in `Math`.
MathUtils() - Constructor for class org.apache.commons.math.util.MathUtils
  Private Constructor
MatrixIndexException - Exception in org.apache.commons.math.linear
  Thrown when an operation addresses a matrix coordinate (row, col) which is outside of the dimensions of a matrix.
MatrixIndexException(String, Object...) - Constructor for exception org.apache.commons.math.linear.MatrixIndexException
  Constructs a new instance with specified formatted detail message.
MatrixUtils - Class in org.apache.commons.math.linear
  A collection of static methods that operate on or return matrices.
MatrixUtils() - Constructor for class org.apache.commons.math.linear.MatrixUtils
  Private constructor.
MatrixUtils.BigFractionMatrixConverter - Class in org.apache.commons.math.linear
  Converter for `FieldMatrix`/`BigFraction`.
MatrixUtils.BigFractionMatrixConverter() - Constructor for class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
  Simple constructor.
MatrixUtils.FractionMatrixConverter - Class in org.apache.commons.math.linear
  Converter for `FieldMatrix`/`Fraction`.
MatrixUtils.FractionMatrixConverter() - Constructor for class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
  Simple constructor.
MatrixVisitorException - Exception in org.apache.commons.math.linear
  Thrown when a visitor encounters an error while processing a matrix entry.
MatrixVisitorException(String, Object[]) - Constructor for exception org.apache.commons.math.linear.MatrixVisitorException
  Constructs a new instance with specified formatted detail message.
max - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Max loaded value
Max - Class in org.apache.commons.math.stat.descriptive.rank
  Returns the maximum of the available values.
Max() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Max
  Create a Max instance
Max(Max) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Max
  Copy constructor, creates a new `Max` identical to the `original`
max - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  The maximum value
max - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  max of values that have been added
MAX - Static variable in class org.apache.commons.math.stat.StatUtils
  max
max(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the maximum of the entries in the input array, or `Double.NaN` if the array is empty.
max(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the maximum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
maxCheckInterval - Variable in class org.apache.commons.math.ode.events.EventState
  Maximal time interval between events handler checks.
maxChecks - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  maximal number of checks for each iteration.
maxCostEval - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Maximal allowed number of cost evaluations.
maxEvaluations - Variable in exception org.apache.commons.math.MaxEvaluationsExceededException
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Maximal number of evaluations allowed.
maxEvaluations - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Maximal number of evaluations allowed.
MaxEvaluationsExceededException - Exception in org.apache.commons.math
  Error thrown when a numerical computation exceeds its allowed number of functions evaluations.
MaxEvaluationsExceededException(int) - Constructor for exception org.apache.commons.math.MaxEvaluationsExceededException
  Constructs an exception with specified formatted detail message.
MaxEvaluationsExceededException(int, String, Object...) - Constructor for exception org.apache.commons.math.MaxEvaluationsExceededException
  Constructs an exception with specified formatted detail message.
maxGenerations - Variable in class org.apache.commons.math.genetics.FixedGenerationCount
  Maximum number of generations (stopping criteria)
maxGrowth - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Maximal growth factor for stepsize control.
maxGrowth - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Maximal growth factor for stepsize control.
maximalIterationCount - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  Maximum number of iterations.
maxImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Maximum statistic implementation - can be reset by setter.
maxImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Maximum statistic implementation - can be reset by setter.
maxImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Maximum statistic implementation - can be reset by setter.
maxIter - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Maximum number of iterations accepted in the implicit QL transformation
maxIter - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  maximal number of iterations for which checks are performed.
maxIterationCount - Variable in class org.apache.commons.math.ode.events.EventState
  Upper limit in the iteration count for event localization.
maxIterations - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Maximum number of iterations for cumulative probability.
maxIterations - Variable in exception org.apache.commons.math.MaxIterationsExceededException
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Maximal number of iterations allowed.
maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Maximal number of iterations allowed.
MaxIterationsExceededException - Exception in org.apache.commons.math
  Error thrown when a numerical computation exceeds its allowed number of iterations.
MaxIterationsExceededException(int) - Constructor for exception org.apache.commons.math.MaxIterationsExceededException
  Constructs an exception with specified formatted detail message.
MaxIterationsExceededException(int, String, Object...) - Constructor for exception org.apache.commons.math.MaxIterationsExceededException
  Constructs an exception with specified formatted detail message.
maxOrder - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  maximal order.
maxStep - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Maximal step.
mdfft(Object, boolean) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Performs a multi-dimensional Fourier transform on a given array.
mdfft(FastFourierTransformer.MultiDimensionalComplexMatrix, boolean, int, int[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Performs one dimension of a multi-dimensional Fourier transform.
mean - Variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  The mean of this distribution.
mean - Variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  The mean of this distribution.
mean - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Holds the Poisson mean for the distribution.
mean - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Mean vector.
mean - Variable in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
  Mean vector.
Mean - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the arithmetic mean of a set of values.
Mean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
  Constructs a Mean.
Mean(FirstMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
  Constructs a Mean with an External Moment.
Mean(Mean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
  Copy constructor, creates a new `Mean` identical to the `original`
mean - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  The sample mean
mean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  mean of values that have been added
MEAN - Static variable in class org.apache.commons.math.stat.StatUtils
  mean
mean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the arithmetic mean of the entries in the input array, or `Double.NaN` if the array is empty.
mean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the arithmetic mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
meanDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the mean of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
meanImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Mean statistic implementation - can be reset by setter.
meanImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Mean statistic implementation - can be reset by setter.
meanImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Mean statistic implementation - can be reset by setter.
means - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
  Means for each component.
measuredValue - Variable in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Value of the measurements.
measurements - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Array of measurements.
measurements - Variable in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Measurements.
median - Variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
  The median of this distribution.
Median - Class in org.apache.commons.math.stat.descriptive.rank
  Returns the median of the available values.
Median() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Median
  Default constructor.
Median(Median) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Median
  Copy constructor, creates a new `Median` identical to the `original`
MersenneTwister - Class in org.apache.commons.math.random
  This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.
MersenneTwister() - Constructor for class org.apache.commons.math.random.MersenneTwister
  Creates a new random number generator.
MersenneTwister(int) - Constructor for class org.apache.commons.math.random.MersenneTwister
  Creates a new random number generator using a single int seed.
MersenneTwister(int[]) - Constructor for class org.apache.commons.math.random.MersenneTwister
  Creates a new random number generator using an int array seed.
MersenneTwister(long) - Constructor for class org.apache.commons.math.random.MersenneTwister
  Creates a new random number generator using a single long seed.
MessagesResources_fr - Class in org.apache.commons.math
  French localization message resources for the commons-math library.
MessagesResources_fr() - Constructor for class org.apache.commons.math.MessagesResources_fr
  Simple constructor.
METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Integrator method name.
METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Integrator method name.
METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Integrator method name.
METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Integrator method name.
microsphere - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
  Internal accounting data for the interpolation algorithm.
microsphereElements - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Number of surface elements of the microsphere.
MicrosphereInterpolatingFunction - Class in org.apache.commons.math.analysis.interpolation
  Interpolating function that implements the Microsphere Projection.
MicrosphereInterpolatingFunction(double[][], double[], int, int, UnitSphereRandomVectorGenerator) - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
MicrosphereInterpolatingFunction.MicrosphereSurfaceElement - Class in org.apache.commons.math.analysis.interpolation
  Class for storing the accounting data needed to perform the microsphere projection.
MicrosphereInterpolatingFunction.MicrosphereSurfaceElement(double[]) - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
MicrosphereInterpolator - Class in org.apache.commons.math.analysis.interpolation
  Interpolator that implements the algorithm described in William Dudziak's MS thesis
MicrosphereInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Create a microsphere interpolator with default settings.
MicrosphereInterpolator(int, int) - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Create a microsphere interpolator.
midpoint(double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  Compute the midpoint of two values.
MidpointIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a second order Runge-Kutta integrator for Ordinary Differential Equations.
MidpointIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Simple constructor.
MidpointStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a step interpolator for second order Runge-Kutta integrator.
MidpointStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
  Simple constructor.
MidpointStepInterpolator(MidpointStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
  Copy constructor.
min - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Min loaded value
Min - Class in org.apache.commons.math.stat.descriptive.rank
  Returns the minimum of the available values.
Min() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Min
  Create a Min instance
Min(Min) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Min
  Copy constructor, creates a new `Min` identical to the `original`
min - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  The minimum value
min - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  min of values that have been added
MIN - Static variable in class org.apache.commons.math.stat.StatUtils
  min
min(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the minimum of the entries in the input array, or `Double.NaN` if the array is empty.
min(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the minimum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
minimalIterationCount - Variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  minimum number of iterations
minImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Minimum statistic implementation - can be reset by setter.
minImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Minimum statistic implementation - can be reset by setter.
minImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Minimum statistic implementation - can be reset by setter.
minReduction - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Minimal reduction factor for stepsize control.
minReduction - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Minimal reduction factor for stepsize control.
minStep - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Minimal step.
MINUS_I - Static variable in class org.apache.commons.math.geometry.Vector3D
  Opposite of the first canonical vector (coordinates: -1, 0, 0).
MINUS_J - Static variable in class org.apache.commons.math.geometry.Vector3D
  Opposite of the second canonical vector (coordinates: 0, -1, 0).
MINUS_K - Static variable in class org.apache.commons.math.geometry.Vector3D
  Opposite of the third canonical vector (coordinates: 0, 0, -1).
MINUS_ONE - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "-1 / 1".
MINUS_ONE - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "-1 / 1".
MISSING_ROOTS_OF_UNITY_MESSAGE - Static variable in class org.apache.commons.math.transform.FastFourierTransformer
  Message for not computed roots of unity.
missingEntries - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Return value for missing entries.
missingEntries - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Return value for missing entries.
mode - Variable in class org.apache.commons.math.random.ValueServer
  mode determines how values are generated.
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Fourth Moment on which this statistic is based
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Mean
  First moment on which this statistic is based.
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Third moment on which this statistic is based
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  SecondMoment is used in incremental calculation of Variance
mt - Variable in class org.apache.commons.math.random.MersenneTwister
  Bytes pool.
mti - Variable in class org.apache.commons.math.random.MersenneTwister
  Current index in the bytes pool.
mu - Variable in class org.apache.commons.math.random.ValueServer
  Mean for use with non-data-driven modes.
mudif - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  interpolation order control parameter.
mulAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Multiply two integers, checking for overflow.
mulAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
  Multiply two long integers, checking for overflow.
MullerSolver - Class in org.apache.commons.math.analysis.solvers
  Implements the Muller's Method for root finding of real univariate functions.
MullerSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.MullerSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `MullerSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
MullerSolver() - Constructor for class org.apache.commons.math.analysis.solvers.MullerSolver
  Construct a solver.
multiDimensionalComplexArray - Variable in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Storage array.
MultiDirectional - Class in org.apache.commons.math.optimization.direct
  This class implements the multi-directional direct search method.
MultiDirectional() - Constructor for class org.apache.commons.math.optimization.direct.MultiDirectional
  Build a multi-directional optimizer with default coefficients.
MultiDirectional(double, double) - Constructor for class org.apache.commons.math.optimization.direct.MultiDirectional
  Build a multi-directional optimizer with specified coefficients.
MultipleLinearRegression - Interface in org.apache.commons.math.stat.regression
  The multiple linear regression can be represented in matrix-notation.
MULTIPLICATIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
  multiplicative expansion mode
MULTIPLY - Static variable in class org.apache.commons.math.analysis.BinaryFunction
  The * operator method wrapped as a `BinaryFunction`.
multiply(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function multiplying the instance and another function.
multiply(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function scaling the instance by a constant factor.
multiply(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Multiply the instance by a polynomial.
multiply(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the product of this complex number and the given complex number.
multiply(double) - Method in class org.apache.commons.math.complex.Complex
  Return the product of this complex number and the given scalar number.
multiply(T) - Method in interface org.apache.commons.math.FieldElement
  Compute this × a.
multiply(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
  Multiplies the value of this fraction by the passed `BigInteger`, returning the result in reduced form.
multiply(int) - Method in class org.apache.commons.math.fraction.BigFraction
  Multiply the value of this fraction by the passed `int`, returning the result in reduced form.
multiply(long) - Method in class org.apache.commons.math.fraction.BigFraction
  Multiply the value of this fraction by the passed `long`, returning the result in reduced form.
multiply(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
  Multiplies the value of this fraction by another, returning the result in reduced form.
multiply(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
  Multiplies the value of this fraction by another, returning the result in reduced form.
multiply(int) - Method in class org.apache.commons.math.fraction.Fraction
  Multiply the fraction by an integer.
multiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the result of postmultiplying this by m.
multiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the result of postmultiplying this by m.
multiply(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the result of postmultiplying this by `m`.
multiply(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the result of postmultiplying this by m.
multiply(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the result of postmultiplying this by `m`.
multiply(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the result of postmultiplying this by m.
multiply(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result of postmultiplying this by `m`.
multiply(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result of postmultiplying this by `m`.
multiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the result of postmultiplying this by m.
multiply(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the result of postmultiplying this by m.
multiply(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the result of postmultiplying this by m.
multiply(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Returns the result of postmultiplying this by m.
multiply(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the result of postmultiplying this by m.
multiply(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the result of postmultiplying this by `m`.
multiply(BigReal) - Method in class org.apache.commons.math.util.BigReal
  Compute this × a.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Change an entry in the specified row and column.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Change an entry in the specified row and column.
MultiStartDifferentiableMultivariateRealOptimizer - Class in org.apache.commons.math.optimization
  Special implementation of the `DifferentiableMultivariateRealOptimizer` interface adding multi-start features to an existing optimizer.
MultiStartDifferentiableMultivariateRealOptimizer(DifferentiableMultivariateRealOptimizer, int, RandomVectorGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Create a multi-start optimizer from a single-start optimizer
MultiStartDifferentiableMultivariateVectorialOptimizer - Class in org.apache.commons.math.optimization
  Special implementation of the `DifferentiableMultivariateVectorialOptimizer` interface adding multi-start features to an existing optimizer.
MultiStartDifferentiableMultivariateVectorialOptimizer(DifferentiableMultivariateVectorialOptimizer, int, RandomVectorGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Create a multi-start optimizer from a single-start optimizer
MultiStartMultivariateRealOptimizer - Class in org.apache.commons.math.optimization
  Special implementation of the `MultivariateRealOptimizer` interface adding multi-start features to an existing optimizer.
MultiStartMultivariateRealOptimizer(MultivariateRealOptimizer, int, RandomVectorGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Create a multi-start optimizer from a single-start optimizer
MultiStartUnivariateRealOptimizer - Class in org.apache.commons.math.optimization
  Special implementation of the `UnivariateRealOptimizer` interface adding multi-start features to an existing optimizer.
MultiStartUnivariateRealOptimizer(UnivariateRealOptimizer, int, RandomGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Create a multi-start optimizer from a single-start optimizer
MultistepIntegrator - Class in org.apache.commons.math.ode
  This class is the base class for multistep integrators for Ordinary Differential Equations.
MultistepIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator
  Build a multistep integrator with the given stepsize bounds.
MultistepIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator
  Build a multistep integrator with the given stepsize bounds.
MultistepIntegrator.CountingDifferentialEquations - Class in org.apache.commons.math.ode
  Wrapper for differential equations, ensuring start evaluations are counted.
MultistepIntegrator.CountingDifferentialEquations(int) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
  Simple constructor.
MultistepIntegrator.InitializationCompletedMarkerException - Exception in org.apache.commons.math.ode
  Marker exception used ONLY to stop the starter integrator after first step.
MultistepIntegrator.InitializationCompletedMarkerException() - Constructor for exception org.apache.commons.math.ode.MultistepIntegrator.InitializationCompletedMarkerException
  Simple constructor.
MultistepIntegrator.NordsieckInitializer - Class in org.apache.commons.math.ode
  Specialized step handler storing the first step.
MultistepIntegrator.NordsieckInitializer(int) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
  Simple constructor.
MultistepIntegrator.NordsieckTransformer - Interface in org.apache.commons.math.ode
  Transformer used to convert the first step to Nordsieck representation.
MultivariateMatrixFunction - Interface in org.apache.commons.math.analysis
  An interface representing a multivariate matrix function.
MultivariateRealFunction - Interface in org.apache.commons.math.analysis
  An interface representing a multivariate real function.
MultivariateRealInterpolator - Interface in org.apache.commons.math.analysis.interpolation
  Interface representing a univariate real interpolating function.
MultivariateRealOptimizer - Interface in org.apache.commons.math.optimization
  This interface represents an optimization algorithm for `scalar objective functions`.
MultivariateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
  Computes summary statistics for a stream of n-tuples added using the `addValue` method.
MultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Construct a MultivariateSummaryStatistics instance
MultivariateVectorialFunction - Interface in org.apache.commons.math.analysis
  An interface representing a multivariate vectorial function.
mutate(Chromosome) - Method in class org.apache.commons.math.genetics.BinaryMutation
  Mutate the given chromosome.
mutate(Chromosome) - Method in interface org.apache.commons.math.genetics.MutationPolicy
  Mutate the given chromosome.
mutate(Chromosome) - Method in class org.apache.commons.math.genetics.RandomKeyMutation
  Mutate the given chromosome.
mutationPolicy - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  the mutation policy used by the algorithm.
MutationPolicy - Interface in org.apache.commons.math.genetics
  Algorithm used to mutate a chrommosome.
mutationRate - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  the rate of mutation for the algorithm.

## N

n - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Number of spline segments = number of polynomials = number of partition points - 1
n - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Number of columns of the initial matrix.
n - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Dimension of the original ODE.
n - Variable in class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
  Problem dimension.
N - Static variable in class org.apache.commons.math.random.MersenneTwister
  Size of the bytes pool.
n - Variable in class org.apache.commons.math.stat.correlation.Covariance
  Number of observations (length of covariate vectors)
n - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Count of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Number of vectors in the sample.
n - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Count of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.rank.Max
  Number of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.rank.Min
  Number of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  The number of observations in the sample
n - Variable in class org.apache.commons.math.stat.descriptive.summary.Product
  The number of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.summary.Sum
n - Variable in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Number of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
n - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  count of values that have been added
n - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  number of observations
name - Variable in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Name of the parameter
name - Variable in class org.apache.commons.math.geometry.RotationOrder
  Name of the rotations order.
name - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Name of the method.
NaN - Static variable in class org.apache.commons.math.complex.Complex
  A complex number representing "NaN + NaNi"
NaN - Static variable in class org.apache.commons.math.geometry.Vector3D
  A vector with all coordinates set to NaN.
NAN_GAP - Static variable in class org.apache.commons.math.util.MathUtils
  Gap between NaN and regular numbers.
NaNStrategy - Enum in org.apache.commons.math.stat.ranking
  Strategies for handling NaN values in rank transformations.
NaNStrategy() - Constructor for enum org.apache.commons.math.stat.ranking.NaNStrategy
nanStrategy - Variable in class org.apache.commons.math.stat.ranking.NaturalRanking
  NaN strategy - defaults to NaNs maximal
NaturalRanking - Class in org.apache.commons.math.stat.ranking
  Ranking based on the natural ordering on doubles.
NaturalRanking() - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
  Create a NaturalRanking with default strategies for handling ties and NaNs.
NaturalRanking(TiesStrategy) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
  Create a NaturalRanking with the given TiesStrategy.
NaturalRanking(NaNStrategy) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
  Create a NaturalRanking with the given NaNStrategy.
NaturalRanking(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
  Create a NaturalRanking with the given NaNStrategy and TiesStrategy.
NaturalRanking(RandomGenerator) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
  Create a NaturalRanking with TiesStrategy.RANDOM and the given RandomGenerator as the source of random data.
NaturalRanking(NaNStrategy, RandomGenerator) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
  Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data.
NaturalRanking.IntDoublePair - Class in org.apache.commons.math.stat.ranking
  Represents the position of a double value in an ordering.
NaturalRanking.IntDoublePair(double, int) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
  Construct an IntDoublePair with the given value and position.
NB - Static variable in class org.apache.commons.math.util.MathUtils
  -1.0 cast as a byte.
nDev - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Deviation of most recently added value from previous first moment, normalized by previous sample size.
nDevSq - Variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Square of deviation of most recently added value from previous first moment, normalized by previous sample size.
NEGATE - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The - operator wrapped as a `ComposableFunction`.
negate() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Negate the instance.
negate() - Method in class org.apache.commons.math.complex.Complex
  Return the additive inverse of this complex number.
negate() - Method in class org.apache.commons.math.fraction.BigFraction
  Return the additive inverse of this fraction, returning the result in reduced form.
negate() - Method in class org.apache.commons.math.fraction.Fraction
  Return the additive inverse of this fraction.
negate() - Method in class org.apache.commons.math.geometry.Vector3D
  Get the opposite of the instance.
NEGATIVE_INFINITY - Static variable in class org.apache.commons.math.geometry.Vector3D
  A vector with all coordinates set to negative infinity.
NEGATIVE_VAR_COLUMN_LABEL - Static variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Column label for negative vars.
NelderMead - Class in org.apache.commons.math.optimization.direct
  This class implements the Nelder-Mead direct search method.
NelderMead() - Constructor for class org.apache.commons.math.optimization.direct.NelderMead
  Build a Nelder-Mead optimizer with default coefficients.
NelderMead(double, double, double, double) - Constructor for class org.apache.commons.math.optimization.direct.NelderMead
  Build a Nelder-Mead optimizer with specified coefficients.
NevilleInterpolator - Class in org.apache.commons.math.analysis.interpolation
  Implements the Neville's Algorithm for interpolation of real univariate functions.
NevilleInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.NevilleInterpolator
newBisectionSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver`.
newBisectionSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver`.
newBrentSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver`.
newBrentSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver`.
newCovarianceData(double[][]) - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Add the covariance data.
newDefaultSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver`.
newDefaultSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver`.
newFixedLengthChromosome(List<T>) - Method in class org.apache.commons.math.genetics.AbstractListChromosome
  Creates a new instance of the same class as `this` is, with a given `arrayRepresentation`.
newInstance() - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Create a new factory.
newNewtonSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver`.
newNewtonSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver`.
newSampleData(double[], int, int) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Loads model x and y sample data from a flat array of data, overriding any previous sample.
newSampleData(double[], double[][], double[][]) - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Replace sample data, overriding any previous sample.
newSampleData(double[], double[][]) - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Loads model x and y sample data, overriding any previous sample.
newSampleData(double[], int, int) - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Loads model x and y sample data from a flat array of data, overriding any previous sample.
newSecantSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver`.
newSecantSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver`.
NewtonSolver - Class in org.apache.commons.math.analysis.solvers
  Implements Newton's Method for finding zeros of real univariate functions.
NewtonSolver(DifferentiableUnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.NewtonSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `NewtonSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
NewtonSolver() - Constructor for class org.apache.commons.math.analysis.solvers.NewtonSolver
  Construct a solver.
newXSampleData(double[][]) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Loads new x sample data, overriding any previous sample
newXSampleData(double[][]) - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Loads new x sample data, overriding any previous sample
newYSampleData(double[]) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Loads new y sample data, overriding any previous sample
next - Variable in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
  Next entry.
next() - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
next() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
next(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Generate next pseudorandom number.
next(int) - Method in class org.apache.commons.math.random.MersenneTwister
  Generate next pseudorandom number.
next - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Index of next element.
next - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Index of next element.
nextAction - Variable in class org.apache.commons.math.ode.events.EventState
  Next action indicator.
nextAfter(double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Get the next machine representable number after a number, moving in the direction of another number.
nextBoolean() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns the next pseudorandom, uniformly distributed `boolean` value from this random number generator's sequence.
nextBoolean() - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns the next pseudorandom, uniformly distributed `boolean` value from this random number generator's sequence.
nextBoolean() - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns the next pseudorandom, uniformly distributed `boolean` value from this random number generator's sequence.
nextBoolean() - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns the next pseudorandom, uniformly distributed `boolean` value from this random number generator's sequence.
nextBytes(byte[]) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Generates random bytes and places them into a user-supplied byte array.
nextBytes(byte[]) - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Generates random bytes and places them into a user-supplied byte array.
nextBytes(byte[]) - Method in class org.apache.commons.math.random.RandomAdaptor
  Generates random bytes and places them into a user-supplied byte array.
nextBytes(byte[]) - Method in interface org.apache.commons.math.random.RandomGenerator
  Generates random bytes and places them into a user-supplied byte array.
nextDouble() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns the next pseudorandom, uniformly distributed `double` value between `0.0` and `1.0` from this random number generator's sequence.
nextDouble() - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns the next pseudorandom, uniformly distributed `double` value between `0.0` and `1.0` from this random number generator's sequence.
nextDouble() - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns the next pseudorandom, uniformly distributed `double` value between `0.0` and `1.0` from this random number generator's sequence.
nextDouble() - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns the next pseudorandom, uniformly distributed `double` value between `0.0` and `1.0` from this random number generator's sequence.
nextExponential(double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random value from the exponential distribution with expected value = `mean`.
nextExponential(double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Returns a random value from an Exponential distribution with the given mean.
nextFloat() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns the next pseudorandom, uniformly distributed `float` value between `0.0` and `1.0` from this random number generator's sequence.
nextFloat() - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns the next pseudorandom, uniformly distributed `float` value between `0.0` and `1.0` from this random number generator's sequence.
nextFloat() - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns the next pseudorandom, uniformly distributed `float` value between `0.0` and `1.0` from this random number generator's sequence.
nextFloat() - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns the next pseudorandom, uniformly distributed `float` value between `0.0` and `1.0` from this random number generator's sequence.
nextGaussian() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns the next pseudorandom, Gaussian ("normally") distributed `double` value with mean `0.0` and standard deviation `1.0` from this random number generator's sequence.
nextGaussian - Variable in class org.apache.commons.math.random.BitsStreamGenerator
  Next gaussian.
nextGaussian() - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns the next pseudorandom, Gaussian ("normally") distributed `double` value with mean `0.0` and standard deviation `1.0` from this random number generator's sequence.
nextGaussian() - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns the next pseudorandom, Gaussian ("normally") distributed `double` value with mean `0.0` and standard deviation `1.0` from this random number generator's sequence.
nextGaussian(double, double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random value from the Normal (or Gaussian) distribution with the given mean and standard deviation.
nextGaussian(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random value from a Normal (a.k.a.
nextGaussian() - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns the next pseudorandom, Gaussian ("normally") distributed `double` value with mean `0.0` and standard deviation `1.0` from this random number generator's sequence.
nextGeneration() - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
  Start the population for the next generation.
nextGeneration(Population) - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Evolve the given population into the next generation.
nextGeneration() - Method in interface org.apache.commons.math.genetics.Population
  Start the population for the next generation.
nextHexString(int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random string of hex characters of length `len`.
nextHexString(int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generates a random string of hex characters of length `len`.
nextIndex(int, int) - Method in class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
  Compute the next index of an array, clipping if necessary.
nextInt() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns the next pseudorandom, uniformly distributed `int` value from this random number generator's sequence.
nextInt(int) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns a pseudorandom, uniformly distributed `int` value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
nextInt() - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns the next pseudorandom, uniformly distributed `int` value from this random number generator's sequence.
nextInt(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns a pseudorandom, uniformly distributed `int` value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
nextInt() - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns the next pseudorandom, uniformly distributed `int` value from this random number generator's sequence.
nextInt(int) - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns a pseudorandom, uniformly distributed `int` value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
nextInt(int, int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included).
nextInt(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random int value uniformly distributed between `lower` and `upper`, inclusive.
nextInt() - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns the next pseudorandom, uniformly distributed `int` value from this random number generator's sequence.
nextInt(int) - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns a pseudorandom, uniformly distributed `int` value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
nextLong() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Returns the next pseudorandom, uniformly distributed `long` value from this random number generator's sequence.
nextLong() - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Returns the next pseudorandom, uniformly distributed `long` value from this random number generator's sequence.
nextLong() - Method in class org.apache.commons.math.random.RandomAdaptor
  Returns the next pseudorandom, uniformly distributed `long` value from this random number generator's sequence.
nextLong(long, long) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included).
nextLong(long, long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random long value uniformly distributed between `lower` and `upper`, inclusive.
nextLong() - Method in interface org.apache.commons.math.random.RandomGenerator
  Returns the next pseudorandom, uniformly distributed `long` value from this random number generator's sequence.
nextNonzero(double[], int) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Returns the smallest index j such that j > i && (j==weights.length || weights[j] != 0)
nextNormalizedDouble() - Method in class org.apache.commons.math.random.GaussianRandomGenerator
  Generate a random scalar with null mean and unit standard deviation.
nextNormalizedDouble() - Method in interface org.apache.commons.math.random.NormalizedRandomGenerator
  Generate a random scalar with null mean and unit standard deviation.
nextNormalizedDouble() - Method in class org.apache.commons.math.random.UniformRandomGenerator
  Generate a random scalar with null mean and unit standard deviation.
nextPermutation(int, int) - Method in interface org.apache.commons.math.random.RandomData
  Generates an integer array of length `k` whose entries are selected randomly, without repetition, from the integers `0 through n-1` (inclusive).
nextPermutation(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generates an integer array of length `k` whose entries are selected randomly, without repetition, from the integers `0 through n-1` (inclusive).
nextPoisson(double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random value from the Poisson distribution with the given mean.
nextPoisson(double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generates a random value from the Poisson distribution with the given mean.
nextPowerOfTwo(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Find the smallest power of two greater than the input value
nextPowerOfTwo(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Find the smallest power of two greater than the input value
nextSample(Collection<?>, int) - Method in interface org.apache.commons.math.random.RandomData
  Returns an array of `k` objects selected randomly from the Collection `c`.
nextSample(Collection<?>, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Uses a 2-cycle permutation shuffle to generate a random permutation.
nextSecureHexString(int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random string of hex characters from a secure random sequence.
nextSecureHexString(int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generates a random string of hex characters from a secure random sequence.
nextSecureInt(int, int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included) from a secure random sequence.
nextSecureInt(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random int value uniformly distributed between `lower` and `upper`, inclusive.
nextSecureLong(long, long) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random long integer between `lower` and `upper` (endpoints included).
nextSecureLong(long, long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random long value uniformly distributed between `lower` and `upper`, inclusive.
nextUniform(double, double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random value from the open interval (`lower`,`upper`) (i.e., endpoints excluded).
nextUniform(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generates a uniformly distributed random value from the open interval (`lower`,`upper`) (i.e., endpoints excluded).
nextVector() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Generate a correlated random vector.
nextVector() - Method in interface org.apache.commons.math.random.RandomVectorGenerator
  Generate a random vector.
nextVector() - Method in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
  Generate an uncorrelated random vector.
nextVector() - Method in class org.apache.commons.math.random.UnitSphereRandomVectorGenerator
  Generate a random vector.
NO_ENTRY_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Message for no entry at selected indices.
NO_ENTRY_MESSAGE - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Message for no entry at selected indices.
nObs - Variable in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  number of observations
NoFeasibleSolutionException - Exception in org.apache.commons.math.optimization.linear
  This class represents exceptions thrown by optimizers when no solution fulfills the constraints.
NoFeasibleSolutionException() - Constructor for exception org.apache.commons.math.optimization.linear.NoFeasibleSolutionException
  Simple constructor using a default message.
NON_BRACKETING_MESSAGE - Static variable in class org.apache.commons.math.analysis.solvers.BrentSolver
  Error message for non-bracketing interval.
NON_FITTING_POSITION_AND_SIZE_MESSAGE - Static variable in class org.apache.commons.math.linear.ArrayRealVector
  Message for non fitting position and size.
NON_POLYNOMIAL_FUNCTION_MESSAGE - Static variable in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Message for non-polynomial function.
NON_POSITIVE_DEGREE_MESSAGE - Static variable in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Message for non-positive degree.
NON_POSITIVE_DEGREES_OF_FREEDOM_MESSAGE - Static variable in class org.apache.commons.math.distribution.FDistributionImpl
  Message for non positive degrees of freddom.
NonLinearConjugateGradientOptimizer - Class in org.apache.commons.math.optimization.general
  Non-linear conjugate gradient optimizer.
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula) - Constructor for class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Simple constructor with default settings.
NonLinearConjugateGradientOptimizer.IdentityPreconditioner - Class in org.apache.commons.math.optimization.general
  Default identity preconditioner.
NonLinearConjugateGradientOptimizer.IdentityPreconditioner() - Constructor for class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.IdentityPreconditioner
NonLinearConjugateGradientOptimizer.LineSearchFunction - Class in org.apache.commons.math.optimization.general
  Internal class for line search.
NonLinearConjugateGradientOptimizer.LineSearchFunction(double[]) - Constructor for class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.LineSearchFunction
  Simple constructor.
nonNegative - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Whether to restrict the variables to non-negative values.
nonSingular - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Singularity indicator.
NonSquareMatrixException - Exception in org.apache.commons.math.linear
  Thrown when an operation defined only for square matrices is applied to non-square ones.
NonSquareMatrixException(int, int) - Constructor for exception org.apache.commons.math.linear.NonSquareMatrixException
  Construct an exception with the given message.
nordsieck - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Nordsieck matrix of the higher scaled derivatives.
nordsieck - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Nordsieck vector.
NordsieckStepInterpolator - Class in org.apache.commons.math.ode.sampling
  This class implements an interpolator for integrators using Nordsieck representation.
NordsieckStepInterpolator() - Constructor for class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Simple constructor.
NordsieckStepInterpolator(NordsieckStepInterpolator) - Constructor for class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Copy constructor.
normal - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Normal vector characterizing a surface element.
normal() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Return the normal vector.
normal - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Distribution used to compute normal approximation.
normalApproximateProbability(int) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Calculates the Poisson distribution function using a normal approximation.
normalApproximateProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Calculates the Poisson distribution function using a normal approximation.
NormalDistribution - Interface in org.apache.commons.math.distribution
  Normal (Gauss) Distribution.
NormalDistributionImpl - Class in org.apache.commons.math.distribution
  Default implementation of `NormalDistribution`.
NormalDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
  Create a normal distribution using the given mean and standard deviation.
NormalDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
  Create a normal distribution using the given mean, standard deviation and inverse cumulative distribution accuracy.
NormalDistributionImpl() - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
  Creates normal distribution with the mean equal to zero and standard deviation equal to one.
normalize() - Method in class org.apache.commons.math.geometry.Vector3D
  Get a normalized vector aligned with the instance.
normalize(LinearConstraint) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get a new equation equivalent to this one with a positive right hand side.
normalizeAngle(double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Normalize an angle in a 2&pi wide interval around a center value.
normalizeArray(double[], double) - Static method in class org.apache.commons.math.util.MathUtils
  Normalizes an array to make it sum to a specified value.
normalizeConstraints(Collection<LinearConstraint>) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get new versions of the constraints which have positive right hand sides.
normalized - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Storage for the normalized vector.
NormalizedRandomGenerator - Interface in org.apache.commons.math.random
  This interface represent a normalized random generator for scalars.
NOT_POWER_OF_TWO_MESSAGE - Static variable in class org.apache.commons.math.transform.FastFourierTransformer
  Message for not power of 2.
NotARotationMatrixException - Exception in org.apache.commons.math.geometry
  This class represents exceptions thrown while building rotations from matrices.
NotARotationMatrixException(String, Object...) - Constructor for exception org.apache.commons.math.geometry.NotARotationMatrixException
  Simple constructor.
NotPositiveDefiniteMatrixException - Exception in org.apache.commons.math.linear
  This class represents exceptions thrown when a matrix expected to be positive definite is not.
NotPositiveDefiniteMatrixException() - Constructor for exception org.apache.commons.math.linear.NotPositiveDefiniteMatrixException
  Simple constructor.
NotSymmetricMatrixException - Exception in org.apache.commons.math.linear
  This class represents exceptions thrown when a matrix expected to be symmetric is not
NotSymmetricMatrixException() - Constructor for exception org.apache.commons.math.linear.NotSymmetricMatrixException
  Simple constructor.
NS - Static variable in class org.apache.commons.math.util.MathUtils
  -1.0 cast as a short.
nSteps - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Number of steps of the multistep method (excluding the one being computed).
nthRoot(int) - Method in class org.apache.commons.math.complex.Complex
  Computes the n-th roots of this complex number.
NULL_FRACTION - Static variable in class org.apache.commons.math.fraction.Fraction
  Message for null fraction.
NULL_FUNCTION_MESSAGE - Static variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  Message for null function.
numArtificialVariables - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Number of artificial variables.
numberOfElements - Variable in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Number of elements.
numberOfSuccesses - Variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  The number of successes in the population.
numberOfSuccesses - Variable in class org.apache.commons.math.distribution.PascalDistributionImpl
  The number of successes
numberOfTrials - Variable in class org.apache.commons.math.distribution.BinomialDistributionImpl
  The number of trials.
NumberTransformer - Interface in org.apache.commons.math.util
  Subclasses implementing this interface can transform Objects to doubles.
numDecisionVariables - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Number of decision variables.
numElements - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The number of addressable elements in the array.
numerator - Variable in class org.apache.commons.math.fraction.BigFraction
  The numerator.
numerator - Variable in class org.apache.commons.math.fraction.Fraction
  The numerator.
numeratorDegreesOfFreedom - Variable in class org.apache.commons.math.distribution.FDistributionImpl
  The numerator degrees of freedom
numeratorFormat - Variable in class org.apache.commons.math.fraction.AbstractFormat
  The format used for the numerator.
numGenerations - Variable in class org.apache.commons.math.genetics.FixedGenerationCount
  Number of generations that have passed
numSlackVariables - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Number of slack variables.

## O

objective - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Current objective function value.
objectiveEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Number of evaluations already performed.
observations - Variable in class org.apache.commons.math.optimization.fitting.CurveFitter
  Observed points.
observations - Variable in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Sampled observations.
observations - Variable in class org.apache.commons.math.optimization.LeastSquaresConverter
  Observations to be compared to objective function to compute residuals.
ode - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Raw ODE without jacobians computation.
ode - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Raw equations to integrate.
ODEIntegrator - Interface in org.apache.commons.math.ode
  This interface defines the common parts shared by integrators for first and second order differential equations.
ODEWithJacobians - Interface in org.apache.commons.math.ode.jacobians
  This interface represents `first order differential equations` with parameters and partial derivatives.
of(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Precompose the instance with another function.
OLSMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
  Implements ordinary least squares (OLS) to estimate the parameters of a multiple linear regression model.
OLSMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
omega - Variable in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Guessed pulsation ω.
omega - Variable in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Pulsation ω.
Omega - Variable in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Covariance matrix.
omegaCount - Variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Number of roots of unity.
omegaImaginaryForward - Variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Imaginary part of the roots for forward transform.
omegaImaginaryInverse - Variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Imaginary part of the roots for reverse transform.
OmegaInverse - Variable in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
  Inverse of covariance matrix.
omegaReal - Variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Real part of the roots.
ONE - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The constant function always returning 1.
ONE - Static variable in class org.apache.commons.math.complex.Complex
  A complex number representing "1.0 + 0.0i"
ONE - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "1".
ONE - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "1".
ONE - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. BigDecimal 1
ONE - Static variable in class org.apache.commons.math.util.BigReal
  A big real representing 1.
ONE_FIFTH - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "1/5".
ONE_FIFTH - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "1/5".
ONE_HALF - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "1/2".
ONE_HALF - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "1/2".
ONE_HUNDRED_DOUBLE - Static variable in class org.apache.commons.math.fraction.BigFraction
  `BigInteger` representation of 100.
ONE_QUARTER - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "1/4".
ONE_QUARTER - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "1/4".
ONE_THIRD - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "1/3".
ONE_THIRD - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "1/3".
OnePointCrossover<T> - Class in org.apache.commons.math.genetics
  One point crossover policy.
OnePointCrossover() - Constructor for class org.apache.commons.math.genetics.OnePointCrossover
OneWayAnova - Interface in org.apache.commons.math.stat.inference
  An interface for one-way ANOVA (analysis of variance).
oneWayAnova - Static variable in class org.apache.commons.math.stat.inference.TestUtils
  Singleton OneWayAnova instance using default implementation.
oneWayAnovaFValue(Collection<double[]>) - Static method in class org.apache.commons.math.stat.inference.TestUtils
OneWayAnovaImpl - Class in org.apache.commons.math.stat.inference
  Implements one-way ANOVA statistics defined in the `OneWayAnovaImpl` interface.
OneWayAnovaImpl() - Constructor for class org.apache.commons.math.stat.inference.OneWayAnovaImpl
  Default constructor.
OneWayAnovaImpl.AnovaStats - Class in org.apache.commons.math.stat.inference
  Convenience class to pass dfbg,dfwg,F values around within AnovaImpl.
OneWayAnovaImpl.AnovaStats(int, int, double) - Constructor for class org.apache.commons.math.stat.inference.OneWayAnovaImpl.AnovaStats
  Constructor
oneWayAnovaPValue(Collection<double[]>) - Static method in class org.apache.commons.math.stat.inference.TestUtils
oneWayAnovaTest(Collection<double[]>, double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
OpenIntToDoubleHashMap - Class in org.apache.commons.math.util
  Open addressed map from int to double.
OpenIntToDoubleHashMap() - Constructor for class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Build an empty map with default size and using NaN for missing entries.
OpenIntToDoubleHashMap(double) - Constructor for class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Build an empty map with default size
OpenIntToDoubleHashMap(int) - Constructor for class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Build an empty map with specified size and using NaN for missing entries.
OpenIntToDoubleHashMap(int, double) - Constructor for class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Build an empty map with specified size.
OpenIntToDoubleHashMap(OpenIntToDoubleHashMap) - Constructor for class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Copy constructor.
OpenIntToDoubleHashMap.Iterator - Class in org.apache.commons.math.util
  Iterator class for the map.
OpenIntToDoubleHashMap.Iterator() - Constructor for class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Simple constructor.
OpenIntToFieldHashMap<T extends FieldElement<T>> - Class in org.apache.commons.math.util
  Open addressed map from int to FieldElement.
OpenIntToFieldHashMap(Field<T>) - Constructor for class org.apache.commons.math.util.OpenIntToFieldHashMap
  Build an empty map with default size and using zero for missing entries.
OpenIntToFieldHashMap(Field<T>, T) - Constructor for class org.apache.commons.math.util.OpenIntToFieldHashMap
  Build an empty map with default size
OpenIntToFieldHashMap(Field<T>, int) - Constructor for class org.apache.commons.math.util.OpenIntToFieldHashMap
  Build an empty map with specified size and using zero for missing entries.
OpenIntToFieldHashMap(Field<T>, int, T) - Constructor for class org.apache.commons.math.util.OpenIntToFieldHashMap
  Build an empty map with specified size.
OpenIntToFieldHashMap(OpenIntToFieldHashMap<T>) - Constructor for class org.apache.commons.math.util.OpenIntToFieldHashMap
  Copy constructor.
OpenIntToFieldHashMap.Iterator - Class in org.apache.commons.math.util
  Iterator class for the map.
OpenIntToFieldHashMap.Iterator() - Constructor for class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Simple constructor.
OpenMapRealMatrix - Class in org.apache.commons.math.linear
  Sparse matrix implementation based on an open addressed map.
OpenMapRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.OpenMapRealMatrix
  Build a sparse matrix with the supplied row and column dimensions.
OpenMapRealMatrix(OpenMapRealMatrix) - Constructor for class org.apache.commons.math.linear.OpenMapRealMatrix
  Build a matrix by copying another one.
OpenMapRealVector - Class in org.apache.commons.math.linear
  This class implements the `RealVector` interface with a `OpenIntToDoubleHashMap` backing store.
OpenMapRealVector() - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Build a 0-length vector.
OpenMapRealVector(int) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Construct a (dimension)-length vector of zeros.
OpenMapRealVector(int, double) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Construct a (dimension)-length vector of zeros, specifying zero tolerance.
OpenMapRealVector(OpenMapRealVector, int) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Build a resized vector, for use with append.
OpenMapRealVector(int, int) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Build a vector with known the sparseness (for advanced use only).
OpenMapRealVector(int, int, double) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Build a vector with known the sparseness and zero tolerance setting (for advanced use only).
OpenMapRealVector(double[]) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Create from a double array.
OpenMapRealVector(double[], double) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Create from a double array, specifying zero tolerance.
OpenMapRealVector(Double[]) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Create from a Double array.
OpenMapRealVector(Double[], double) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Create from a Double array.
OpenMapRealVector(OpenMapRealVector) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Copy constructor.
OpenMapRealVector(RealVector) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector
  Generic copy constructor.
OpenMapRealVector.OpenMapEntry - Class in org.apache.commons.math.linear
  Implementation of `Entry` optimized for OpenMap.
OpenMapRealVector.OpenMapEntry(OpenIntToDoubleHashMap.Iterator) - Constructor for class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
  Build an entry from an iterator point to an element.
OpenMapRealVector.OpenMapSparseIterator - Class in org.apache.commons.math.linear
  Iterator class to do iteration over just the non-zero elements.
OpenMapRealVector.OpenMapSparseIterator() - Constructor for class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
  Simple constructor.
operate(T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the result of multiplying this by the vector `v`.
operate(FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(T[]) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the result of multiplying this by the vector `v`.
operate(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result of multiplying this by the vector `v`.
operate(T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the result of multiplying this by the vector `v`.
operate(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the result of multiplying this by the vector `v`.
oppositeRelationship() - Method in enum org.apache.commons.math.optimization.linear.Relationship
  Get the relationship obtained when multiplying all coefficients by -1.
optima - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Found optima.
optima - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Found optima.
optima - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Found optima.
optima - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Found optima.
optimalStep - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  optimal steps for each order.
optimaValues - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Found function values at optima.
OptimizationException - Exception in org.apache.commons.math.optimization
  This class represents exceptions thrown by optimizers.
OptimizationException(String, Object...) - Constructor for exception org.apache.commons.math.optimization.OptimizationException
  Simple constructor.
OptimizationException(Throwable) - Constructor for exception org.apache.commons.math.optimization.OptimizationException
  Create an exception with a given root cause.
optimize(DifferentiableMultivariateRealFunction, GoalType, double[]) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Optimizes an objective function.
optimize(DifferentiableMultivariateVectorialFunction, double[], double[], double[]) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Optimizes an objective function.
optimize(MultivariateRealFunction, GoalType, double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Optimizes an objective function.
optimize(DifferentiableMultivariateVectorialFunction, double[], double[], double[]) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Optimizes an objective function.
optimize(DifferentiableMultivariateRealFunction, GoalType, double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Optimizes an objective function.
optimize(LinearObjectiveFunction, Collection<LinearConstraint>, GoalType, boolean) - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Optimizes an objective function.
optimize(LinearObjectiveFunction, Collection<LinearConstraint>, GoalType, boolean) - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
  Optimizes an objective function.
optimize(DifferentiableMultivariateRealFunction, GoalType, double[]) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Optimizes an objective function.
optimize(DifferentiableMultivariateVectorialFunction, double[], double[], double[]) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Optimizes an objective function.
optimize(MultivariateRealFunction, GoalType, double[]) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Optimizes an objective function.
optimize(UnivariateRealFunction, GoalType, double, double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Find an optimum in the given interval.
optimize(UnivariateRealFunction, GoalType, double, double, double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Find an optimum in the given interval, start at startValue.
optimize(MultivariateRealFunction, GoalType, double[]) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Optimizes an objective function.
optimize(UnivariateRealFunction, GoalType, double, double, double) - Method in class org.apache.commons.math.optimization.univariate.BrentOptimizer
  Find an optimum in the given interval, start at startValue.
optimize(UnivariateRealFunction, GoalType, double, double) - Method in class org.apache.commons.math.optimization.univariate.BrentOptimizer
  Find an optimum in the given interval.
optimize(UnivariateRealFunction, GoalType, double, double) - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Find an optimum in the given interval.
optimize(UnivariateRealFunction, GoalType, double, double, double) - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Find an optimum in the given interval, start at startValue.
optimizer - Variable in class org.apache.commons.math.optimization.fitting.CurveFitter
  Optimizer to use for the fitting.
optimizer - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Underlying classical optimizer.
optimizer - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Underlying classical optimizer.
optimizer - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Underlying classical optimizer.
optimizer - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Underlying classical optimizer.
orderControl1 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  first order control factor.
orderControl2 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  second order control factor.
org.apache.commons.math - package org.apache.commons.math
  Common classes used throughout the commons-math library.
org.apache.commons.math.analysis - package org.apache.commons.math.analysis
  Parent package for common numerical analysis procedures, including root finding, function interpolation and integration.
org.apache.commons.math.analysis.integration - package org.apache.commons.math.analysis.integration
  Numerical integration (quadrature) algorithms for univariate real functions.
org.apache.commons.math.analysis.interpolation - package org.apache.commons.math.analysis.interpolation
  Univariate real functions interpolation algorithms.
org.apache.commons.math.analysis.polynomials - package org.apache.commons.math.analysis.polynomials
  Univariate real polynomials implementations, seen as differentiable univariate real functions.
org.apache.commons.math.analysis.solvers - package org.apache.commons.math.analysis.solvers
  Root finding algorithms, for univariate real functions.
org.apache.commons.math.complex - package org.apache.commons.math.complex
  Complex number type and implementations of complex transcendental functions.
org.apache.commons.math.distribution - package org.apache.commons.math.distribution
  Implementations of common discrete and continuous distributions.
org.apache.commons.math.estimation - package org.apache.commons.math.estimation
  This package provided classes to solve estimation problems, it is deprecated since 2.0.
org.apache.commons.math.fraction - package org.apache.commons.math.fraction
  Fraction number type and fraction number formatting.
org.apache.commons.math.genetics - package org.apache.commons.math.genetics
  This package provides Genetic Algorithms components and implementations.
org.apache.commons.math.geometry - package org.apache.commons.math.geometry
  This package provides basic 3D geometry components.
org.apache.commons.math.linear - package org.apache.commons.math.linear
  Linear algebra support.
org.apache.commons.math.ode - package org.apache.commons.math.ode
  This package provides classes to solve Ordinary Differential Equations problems.
org.apache.commons.math.ode.events - package org.apache.commons.math.ode.events
  This package provides classes to handle discrete events occurring during Ordinary Differential Equations integration.
org.apache.commons.math.ode.jacobians - package org.apache.commons.math.ode.jacobians
  This package provides classes to solve Ordinary Differential Equations problems and also compute derivatives of the solution.
org.apache.commons.math.ode.nonstiff - package org.apache.commons.math.ode.nonstiff
  This package provides classes to solve non-stiff Ordinary Differential Equations problems.
org.apache.commons.math.ode.sampling - package org.apache.commons.math.ode.sampling
  This package provides classes to handle sampling steps during Ordinary Differential Equations integration.
org.apache.commons.math.optimization - package org.apache.commons.math.optimization
  This package provides common interfaces for the optimization algorithms provided in sub-packages.
org.apache.commons.math.optimization.direct - package org.apache.commons.math.optimization.direct
  This package provides optimization algorithms that don't require derivatives.
org.apache.commons.math.optimization.fitting - package org.apache.commons.math.optimization.fitting
  This package provides classes to perform curve fitting.
org.apache.commons.math.optimization.general - package org.apache.commons.math.optimization.general
  This package provides optimization algorithms that require derivatives.
org.apache.commons.math.optimization.linear - package org.apache.commons.math.optimization.linear
  This package provides optimization algorithms for linear constrained problems.
org.apache.commons.math.optimization.univariate - package org.apache.commons.math.optimization.univariate
  Univariate real functions minimum finding algorithms.
org.apache.commons.math.random - package org.apache.commons.math.random
  Random number and random data generators.
org.apache.commons.math.special - package org.apache.commons.math.special
  Implementations of special functions such as Beta and Gamma.
org.apache.commons.math.stat - package org.apache.commons.math.stat
  Data storage, manipulation and summary routines.
org.apache.commons.math.stat.clustering - package org.apache.commons.math.stat.clustering
  Clustering algorithms
org.apache.commons.math.stat.correlation - package org.apache.commons.math.stat.correlation
  Correlations/Covariance computations.
org.apache.commons.math.stat.descriptive - package org.apache.commons.math.stat.descriptive
  Generic univariate summary statistic objects.
org.apache.commons.math.stat.descriptive.moment - package org.apache.commons.math.stat.descriptive.moment
  Summary statistics based on moments.
org.apache.commons.math.stat.descriptive.rank - package org.apache.commons.math.stat.descriptive.rank
  Summary statistics based on ranks.
org.apache.commons.math.stat.descriptive.summary - package org.apache.commons.math.stat.descriptive.summary
  Other summary statistics.
org.apache.commons.math.stat.inference - package org.apache.commons.math.stat.inference
  Classes providing hypothesis testing and confidence interval construction.
org.apache.commons.math.stat.ranking - package org.apache.commons.math.stat.ranking
  Classes providing rank transformations.
org.apache.commons.math.stat.regression - package org.apache.commons.math.stat.regression
  Statistical routines involving multivariate data.
org.apache.commons.math.transform - package org.apache.commons.math.transform
  Implementations of transform methods, including Fast Fourier transforms.
org.apache.commons.math.util - package org.apache.commons.math.util
  Convenience routines and common data structures used throughout the commons-math library.
orthogonal() - Method in class org.apache.commons.math.geometry.Vector3D
  Get a vector orthogonal to the instance.
orthogonalizeMatrix(double[][], double) - Method in class org.apache.commons.math.geometry.Rotation
  Perfect orthogonality on a 3X3 matrix.
orthoTolerance - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Desired max cosine on the orthogonality between the function vector and the columns of the jacobian.
orthoTolerance - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Desired max cosine on the orthogonality between the function vector and the columns of the jacobian.
OUT_OF_RANGE_POINT - Static variable in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Message for out of range point.
OUT_OF_RANGE_ROOT_INDEX_MESSAGE - Static variable in class org.apache.commons.math.transform.FastFourierTransformer
  Message for out of range root index.
outerProduct(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute the outer product.
outerProduct(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute the outer product.
outerProduct(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the outer product.
outerProduct(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the outer product.
outerProduct(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute the outer product.
outerProduct(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the outer product.
outerProduct(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the outer product.
outerProduct(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute the outer product.
outerProduct(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute the outer product.
outerProduct(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute the outer product.
outerProduct(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute the outer product.
outerProduct(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Compute the outer product.
outerProduct(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Compute the outer product.
outerProduct(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Optimized method to compute outer product when both vectors are sparse.
outerProduct(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute the outer product.
outerProduct(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute the outer product.
OVERFLOW_MESSAGE - Static variable in class org.apache.commons.math.fraction.Fraction
  Message for overflow.

## P

p - Variable in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Deprecated. as of 2.0 the function is not stored anymore in the instance
p - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Parameters array (may be null if parameters dimension from original problem is zero)
pairedT(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
pairedT(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a paired, 2-sample t-statistic based on the data in the input arrays.
pairedT(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a paired, 2-sample t-statistic based on the data in the input arrays.
pairedTTest(double[], double[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
pairedTTest(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
pairedTTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.
pairedTTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
pairedTTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.
pairedTTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
ParameterizedODE - Interface in org.apache.commons.math.ode.jacobians
  This interface represents `first order differential equations` with parameters.
parameters - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Array of parameters.
parameters - Variable in class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Estimated parameters.
parameters - Variable in class org.apache.commons.math.optimization.fitting.HarmonicFitter
  Values for amplitude, pulsation ω and phase φ.
ParametricRealFunction - Interface in org.apache.commons.math.optimization.fitting
  An interface representing a real function that depends on one independent variable plus some extra parameters.
parity - Variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Parity of the permutation associated with the LU decomposition
parRelativeTolerance - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Desired relative error in the approximate solution parameters.
parRelativeTolerance - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Desired relative error in the approximate solution parameters.
parse(String) - Method in class org.apache.commons.math.complex.ComplexFormat
  Parses a string to produce a `Complex` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Parses a string to produce a `Complex` object.
parse(String) - Method in class org.apache.commons.math.fraction.BigFractionFormat
  Parses a string to produce a `BigFraction` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.fraction.BigFractionFormat
  Parses a string to produce a `BigFraction` object.
parse(String) - Method in class org.apache.commons.math.fraction.FractionFormat
  Parses a string to produce a `Fraction` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.fraction.FractionFormat
  Parses a string to produce a `Fraction` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
  Parses a string to produce a `BigFraction` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.fraction.ProperFractionFormat
  Parses a string to produce a `Fraction` object.
parse(String) - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Parses a string to produce a `Vector3D` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Parses a string to produce a `Vector3D` object.
parse(String) - Method in class org.apache.commons.math.linear.RealVectorFormat
  Parses a string to produce a `RealVector` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.linear.RealVectorFormat
  Parses a string to produce a `RealVector` object.
parseAndIgnoreWhitespace(String, ParsePosition) - Static method in class org.apache.commons.math.fraction.AbstractFormat
  Parses `source` until a non-whitespace character is found.
parseAndIgnoreWhitespace(String, ParsePosition) - Method in class org.apache.commons.math.util.CompositeFormat
  Parses `source` until a non-whitespace character is found.
parseFixedstring(String, String, ParsePosition) - Method in class org.apache.commons.math.util.CompositeFormat
  Parse `source` for an expected fixed string.
parseNextBigInteger(String, ParsePosition) - Method in class org.apache.commons.math.fraction.BigFractionFormat
  Parses a string to produce a `BigInteger`.
parseNextCharacter(String, ParsePosition) - Static method in class org.apache.commons.math.fraction.AbstractFormat
  Parses `source` until a non-whitespace character is found.
parseNextCharacter(String, ParsePosition) - Method in class org.apache.commons.math.util.CompositeFormat
  Parses `source` until a non-whitespace character is found.
parseNumber(String, double, ParsePosition) - Method in class org.apache.commons.math.util.CompositeFormat
  Parses `source` for special double values.
parseNumber(String, NumberFormat, ParsePosition) - Method in class org.apache.commons.math.util.CompositeFormat
  Parses `source` for a number.
parseObject(String, ParsePosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Parses a string to produce a object.
parseObject(String, ParsePosition) - Method in class org.apache.commons.math.geometry.Vector3DFormat
  Parses a string to produce a object.
parseObject(String, ParsePosition) - Method in class org.apache.commons.math.linear.RealVectorFormat
  Parses a string to produce a object.
partialDerivative(int) - Method in interface org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction
  Returns the partial derivative of the function with respect to a point coordinate.
PascalDistribution - Interface in org.apache.commons.math.distribution
  The Pascal distribution.
PascalDistributionImpl - Class in org.apache.commons.math.distribution
  The default implementation of `PascalDistribution`.
PascalDistributionImpl(int, double) - Constructor for class org.apache.commons.math.distribution.PascalDistributionImpl
  Create a binomial distribution with the given number of trials and probability of success.
pattern - Variable in exception org.apache.commons.math.MathException
  Pattern used to build the message.
pattern - Variable in exception org.apache.commons.math.MathRuntimeException
  Pattern used to build the message.
PB - Static variable in class org.apache.commons.math.util.MathUtils
  1.0 cast as a byte.
PearsonsCorrelation - Class in org.apache.commons.math.stat.correlation
  Computes Pearson's product-moment correlation coefficients for pairs of arrays or columns of a matrix.
PearsonsCorrelation() - Constructor for class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Create a PearsonsCorrelation instance without data
PearsonsCorrelation(double[][]) - Constructor for class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Create a PearsonsCorrelation from a rectangular array whose columns represent values of variables to be correlated.
PearsonsCorrelation(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Create a PearsonsCorrelation from a RealMatrix whose columns represent variables to be correlated.
PearsonsCorrelation(Covariance) - Constructor for class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Create a PearsonsCorrelation from a `Covariance`.
PearsonsCorrelation(RealMatrix, int) - Constructor for class org.apache.commons.math.stat.correlation.PearsonsCorrelation
  Create a PearsonsCorrelation from a covariance matrix.
pendingEvent - Variable in class org.apache.commons.math.ode.events.EventState
  Indicator of event expected during the step.
pendingEventTime - Variable in class org.apache.commons.math.ode.events.EventState
  Occurrence time of the pending event.
percentageValue() - Method in class org.apache.commons.math.fraction.BigFraction
  Gets the fraction percentage as a `double`.
Percentile - Class in org.apache.commons.math.stat.descriptive.rank
  Provides percentile computation.
Percentile() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Percentile
  Constructs a Percentile with a default quantile value of 50.0.
Percentile(double) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Percentile
  Constructs a Percentile with the specific quantile value.
Percentile(Percentile) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Percentile
  Copy constructor, creates a new `Percentile` identical to the `original`
PERCENTILE - Static variable in class org.apache.commons.math.stat.StatUtils
  percentile
percentile(double[], double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns an estimate of the `p`th percentile of the values in the `values` array.
percentile(double[], int, int, double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns an estimate of the `p`th percentile of the values in the `values` array, starting with the element in (0-based) position `begin` in the array and including `length` values.
percentileImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Percentile statistic implementation - can be reset by setter.
performTest - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  stability check enabling parameter.
permutation - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Columns permutation array.
permutation - Variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Permutation associated with LU decomposition
permutation - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Columns permutation array.
PermutationChromosome<T> - Interface in org.apache.commons.math.genetics
  Interface indicating that the chromosome represents a permutation of objects.
perturb(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Perturb the hash for starting probing.
perturb(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Perturb the hash for starting probing.
PERTURB_SHIFT - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Number of bits to perturb the index when probing for collision resolution.
PERTURB_SHIFT - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Number of bits to perturb the index when probing for collision resolution.
phi - Variable in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Guessed phase φ.
phi - Variable in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Phase φ.
pivot - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Pivot permutation associated with LU decomposition
pivot - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Pivot permutation associated with LU decomposition.
pivot - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Pivot permutation associated with LU decomposition
pivot - Variable in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Pivot permutation associated with LU decomposition.
PLUS_I - Static variable in class org.apache.commons.math.geometry.Vector3D
  First canonical vector (coordinates: 1, 0, 0).
PLUS_J - Static variable in class org.apache.commons.math.geometry.Vector3D
  Second canonical vector (coordinates: 0, 1, 0).
PLUS_K - Static variable in class org.apache.commons.math.geometry.Vector3D
  Third canonical vector (coordinates: 0, 0, 1).
point - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Current point.
point - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Current point set.
point - Variable in class org.apache.commons.math.optimization.RealPointValuePair
  Point coordinates.
point - Variable in class org.apache.commons.math.optimization.VectorialPointValuePair
  Point coordinates.
point - Variable in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
  Point coordinates.
points - Variable in class org.apache.commons.math.stat.clustering.Cluster
  The points contained in this cluster.
PoissonDistribution - Interface in org.apache.commons.math.distribution
  Interface representing the Poisson Distribution.
PoissonDistributionImpl - Class in org.apache.commons.math.distribution
  Implementation for the `PoissonDistribution`.
PoissonDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Create a new Poisson distribution with the given the mean.
PoissonDistributionImpl(double, double, int) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Create a new Poisson distribution with the given mean, convergence criterion and maximum number of iterations.
PoissonDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Create a new Poisson distribution with the given mean and convergence criterion.
PoissonDistributionImpl(double, int) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Create a new Poisson distribution with the given mean and maximum number of iterations.
PoissonDistributionImpl(double, NormalDistribution) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Deprecated. as of 2.1 (to avoid possibly inconsistent state, the "NormalDistribution" will be instantiated internally)
polar2Complex(double, double) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Creates a complex number from the given polar representation.
polynomialDerivative() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Returns the derivative as a PolynomialRealFunction
PolynomialFitter - Class in org.apache.commons.math.optimization.fitting
  This class implements a curve fitting specialized for polynomials.
PolynomialFitter(int, DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.PolynomialFitter
  Simple constructor.
PolynomialFitter.ParametricPolynomial - Class in org.apache.commons.math.optimization.fitting
  Dedicated parametric polynomial class.
PolynomialFitter.ParametricPolynomial() - Constructor for class org.apache.commons.math.optimization.fitting.PolynomialFitter.ParametricPolynomial
PolynomialFunction - Class in org.apache.commons.math.analysis.polynomials
  Immutable representation of a real polynomial function with real coefficients.
PolynomialFunction(double[]) - Constructor for class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Construct a polynomial with the given coefficients.
PolynomialFunctionLagrangeForm - Class in org.apache.commons.math.analysis.polynomials
  Implements the representation of a real polynomial function in Lagrange Form.
PolynomialFunctionLagrangeForm(double[], double[]) - Constructor for class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Construct a Lagrange polynomial with the given abscissas and function values.
PolynomialFunctionNewtonForm - Class in org.apache.commons.math.analysis.polynomials
  Implements the representation of a real polynomial function in Newton Form.
PolynomialFunctionNewtonForm(double[], double[]) - Constructor for class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Construct a Newton polynomial with the given a[] and c[].
polynomials - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  The polynomial functions that make up the spline.
polynomialSplineDerivative() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Returns the derivative of the polynomial spline function as a PolynomialSplineFunction
PolynomialSplineFunction - Class in org.apache.commons.math.analysis.polynomials
  Represents a polynomial spline function.
PolynomialSplineFunction(double[], PolynomialFunction[]) - Constructor for class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Construct a polynomial spline function with the given segment delimiters and interpolating polynomials.
PolynomialsUtils - Class in org.apache.commons.math.analysis.polynomials
  A collection of static methods that operate on or return polynomials.
PolynomialsUtils() - Constructor for class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
  Private constructor, to prevent instantiation.
PolynomialsUtils.RecurrenceCoefficientsGenerator - Interface in org.apache.commons.math.analysis.polynomials
  Interface for recurrence coefficients generation.
polynoms - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Interpolation polynoms.
Population - Interface in org.apache.commons.math.genetics
  A collection of chromosomes that facilitates generational evolution.
populationLimit - Variable in class org.apache.commons.math.genetics.ListPopulation
  maximial size of the population
populationSize - Variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  The population size.
position - Variable in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
  Original position of the pair
POSITIVE_INFINITY - Static variable in class org.apache.commons.math.geometry.Vector3D
  A vector with all coordinates set to positive infinity.
postCompose(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Postcompose the instance with another function.
POW - Static variable in class org.apache.commons.math.analysis.BinaryFunction
  The `Math.pow` method wrapped as a `BinaryFunction`.
pow(Complex) - Method in class org.apache.commons.math.complex.Complex
  Returns of value of this complex number raised to the power of `x`.
pow(int) - Method in class org.apache.commons.math.fraction.BigFraction
  Returns a `integer` whose value is `(thisexponent)`, returning the result in reduced form.
pow(long) - Method in class org.apache.commons.math.fraction.BigFraction
  Returns a `BigFraction` whose value is `(thisexponent)`, returning the result in reduced form.
pow(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
  Returns a `BigFraction` whose value is `(thisexponent)`, returning the result in reduced form.
pow(double) - Method in class org.apache.commons.math.fraction.BigFraction
  Returns a `double` whose value is `(thisexponent)`, returning the result in reduced form.
pow(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Raise an int to an int power.
pow(int, long) - Static method in class org.apache.commons.math.util.MathUtils
  Raise an int to a long power.
pow(long, int) - Static method in class org.apache.commons.math.util.MathUtils
  Raise a long to an int power.
pow(long, long) - Static method in class org.apache.commons.math.util.MathUtils
  Raise a long to a long power.
pow(BigInteger, int) - Static method in class org.apache.commons.math.util.MathUtils
  Raise a BigInteger to an int power.
pow(BigInteger, long) - Static method in class org.apache.commons.math.util.MathUtils
  Raise a BigInteger to a long power.
pow(BigInteger, BigInteger) - Static method in class org.apache.commons.math.util.MathUtils
  Raise a BigInteger to a BigInteger power.
precondition(double[], double[]) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.IdentityPreconditioner
  Precondition a search direction.
precondition(double[], double[]) - Method in interface org.apache.commons.math.optimization.general.Preconditioner
  Precondition a search direction.
preconditioner - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Preconditioner (may be null).
Preconditioner - Interface in org.apache.commons.math.optimization.general
  This interface represents a preconditioner for differentiable scalar objective function optimizers.
predict(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the "predicted" `y` value associated with the supplied `x` value, based on the data that has been added to the model when this method is activated.
prefix - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  Prefix.
prefix - Variable in class org.apache.commons.math.linear.RealVectorFormat
  Prefix.
preMultiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the result premultiplying this by `m`.
preMultiply(T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the result premultiplying this by `m`.
preMultiply(double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(T[]) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(double[]) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the result premultiplying this by `m`.
preMultiply(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result premultiplying this by `m`.
preMultiply(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the result premultiplying this by `m`.
preMultiply(T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result premultiplying this by `m`.
preMultiply(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(double[]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Returns the (row) vector result of premultiplying this by the vector `v`.
previous - Variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Previous state.
previousEventTime - Variable in class org.apache.commons.math.ode.events.EventState
  Occurrence time of the previous event.
previousIndex(int) - Method in class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
  Compute the previous index of an array, clipping if necessary.
previousTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  previous time
printStackTrace() - Method in exception org.apache.commons.math.MathException
  Prints the stack trace of this exception to the standard error stream.
printStackTrace(PrintStream) - Method in exception org.apache.commons.math.MathException
  Prints the stack trace of this exception to the specified stream.
printStackTrace() - Method in exception org.apache.commons.math.MathRuntimeException
  Prints the stack trace of this exception to the standard error stream.
printStackTrace(PrintStream) - Method in exception org.apache.commons.math.MathRuntimeException
  Prints the stack trace of this exception to the specified stream.
probability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  For this distribution, X, this method returns P(X = x).
probability(double) - Method in interface org.apache.commons.math.distribution.DiscreteDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For this distribution, X, this method returns P(X = x).
probability(int, int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For the distribution, X, defined by the given hypergeometric distribution parameters, this method returns P(X = x).
probability(int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  For this distribution, X, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  The probability mass function P(X = x) for a Poisson distribution.
probability(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  The probability mass function P(X = x) for a Zipf distribution.
probabilityOfSuccess - Variable in class org.apache.commons.math.distribution.BinomialDistributionImpl
  The probability of success.
probabilityOfSuccess - Variable in class org.apache.commons.math.distribution.PascalDistributionImpl
  The probability of success
probe(int, int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Compute next probe for collision resolution
probe(int, int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Compute next probe for collision resolution
Product - Class in org.apache.commons.math.stat.descriptive.summary
  Returns the product of the available values.
Product() - Constructor for class org.apache.commons.math.stat.descriptive.summary.Product
  Create a Product instance
Product(Product) - Constructor for class org.apache.commons.math.stat.descriptive.summary.Product
  Copy constructor, creates a new `Product` identical to the `original`
PRODUCT - Static variable in class org.apache.commons.math.stat.StatUtils
  prod
product(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the product of the entries in the input array, or `Double.NaN` if the array is empty.
product(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the product of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
productsSums - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Sums of products for each component.
projection(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Find the orthogonal projection of this vector onto another vector.
projection(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Find the orthogonal projection of this vector onto another vector.
projection(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Find the orthogonal projection of this vector onto another vector.
projection(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Find the orthogonal projection of this vector onto another vector.
projection(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Find the orthogonal projection of this vector onto another vector.
projection(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Find the orthogonal projection of this vector onto another vector.
projection(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Find the orthogonal projection of this vector onto another vector.
projection(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Find the orthogonal projection of this vector onto another vector.
projection(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Find the orthogonal projection of this vector onto another vector.
projection(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Find the orthogonal projection of this vector onto another vector.
projection(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Find the orthogonal projection of this vector onto another vector.
projection(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Find the orthogonal projection of this vector onto another vector.
projection(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Find the orthogonal projection of this vector onto another vector.
projection(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Find the orthogonal projection of this vector onto another vector.
projection(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Find the orthogonal projection of this vector onto another vector.
ProperBigFractionFormat - Class in org.apache.commons.math.fraction
  Formats a BigFraction number in proper format.
ProperBigFractionFormat() - Constructor for class org.apache.commons.math.fraction.ProperBigFractionFormat
  Create a proper formatting instance with the default number format for the whole, numerator, and denominator.
ProperBigFractionFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.ProperBigFractionFormat
  Create a proper formatting instance with a custom number format for the whole, numerator, and denominator.
ProperBigFractionFormat(NumberFormat, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.ProperBigFractionFormat
  Create a proper formatting instance with a custom number format for each of the whole, numerator, and denominator.
ProperFractionFormat - Class in org.apache.commons.math.fraction
  Formats a Fraction number in proper format.
ProperFractionFormat() - Constructor for class org.apache.commons.math.fraction.ProperFractionFormat
  Create a proper formatting instance with the default number format for the whole, numerator, and denominator.
ProperFractionFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.ProperFractionFormat
  Create a proper formatting instance with a custom number format for the whole, numerator, and denominator.
ProperFractionFormat(NumberFormat, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.ProperFractionFormat
  Create a proper formatting instance with a custom number format for each of the whole, numerator, and denominator.
prototype - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Prototype of the step interpolator.
prototype - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Prototype of the step interpolator.
PS - Static variable in class org.apache.commons.math.util.MathUtils
  1.0 cast as a short.
pseudoInverse - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Pseudo-inverse of the initial matrix.
put(int, double) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Put a value associated with a key in the map.
put(int, T) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Put a value associated with a key in the map.
putTransformer(Class<?>, NumberTransformer) - Method in class org.apache.commons.math.util.TransformerMap
  Sets a Class to Transformer Mapping in the Map.

## Q

q0 - Variable in class org.apache.commons.math.geometry.Rotation
  Scalar coordinate of the quaternion.
q1 - Variable in class org.apache.commons.math.geometry.Rotation
  First coordinate of the vectorial part of the quaternion.
q2 - Variable in class org.apache.commons.math.geometry.Rotation
  Second coordinate of the vectorial part of the quaternion.
q3 - Variable in class org.apache.commons.math.geometry.Rotation
  Third coordinate of the vectorial part of the quaternion.
qr - Variable in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Cached QR decomposition of X matrix
qrDecomposition() - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Decompose a matrix A as A.P = Q.R using Householder transforms.
QRDecomposition - Interface in org.apache.commons.math.linear
  An interface to classes that implement an algorithm to calculate the QR-decomposition of a real matrix.
qrDecomposition() - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Decompose a matrix A as A.P = Q.R using Householder transforms.
QRDecompositionImpl - Class in org.apache.commons.math.linear
  Calculates the QR-decomposition of a matrix.
QRDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.QRDecompositionImpl
  Calculates the QR-decomposition of the given matrix.
QRDecompositionImpl.Solver - Class in org.apache.commons.math.linear
  Specialized solver.
QRDecompositionImpl.Solver(double[][], double[]) - Constructor for class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Build a solver from decomposed matrix.
qrt - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
  A packed TRANSPOSED representation of the QR decomposition.
qrt - Variable in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  A packed TRANSPOSED representation of the QR decomposition.
qTy(double[]) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Compute the product Qt.y for some Q.R.
qTy(double[]) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Compute the product Qt.y for some Q.R.
quantile - Variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Determines what percentile is computed when evaluate() is activated with no quantile argument

## R

rand - Variable in class org.apache.commons.math.random.RandomDataImpl
  underlying random number generator
rand - Variable in class org.apache.commons.math.random.UnitSphereRandomVectorGenerator
  RNG used for generating the individual components of the vectors.
random - Variable in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
  Random generator for choosing initial centers.
RandomAdaptor - Class in org.apache.commons.math.random
  Extension of `java.util.Random` wrapping a `RandomGenerator`.
RandomAdaptor() - Constructor for class org.apache.commons.math.random.RandomAdaptor
  Prevent instantiation without a generator argument
RandomAdaptor(RandomGenerator) - Constructor for class org.apache.commons.math.random.RandomAdaptor
  Construct a RandomAdaptor wrapping the supplied RandomGenerator.
randomBinaryRepresentation(int) - Static method in class org.apache.commons.math.genetics.BinaryChromosome
  Returns a representation of a random binary array of length `length`.
randomData - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  RandomData instance to use in repeated calls to getNext()
RandomData - Interface in org.apache.commons.math.random
  Random data generation utilities.
randomData - Variable in class org.apache.commons.math.random.ValueServer
  RandomDataImpl to use for random data generation.
randomData - Variable in class org.apache.commons.math.stat.ranking.NaturalRanking
  Source of random data - used only when ties strategy is RANDOM
RandomDataImpl - Class in org.apache.commons.math.random
  Implements the `RandomData` interface using a `RandomGenerator` instance to generate non-secure data and a `SecureRandom` instance to provide data for the `nextSecureXxx` methods.
RandomDataImpl() - Constructor for class org.apache.commons.math.random.RandomDataImpl
  Construct a RandomDataImpl.
RandomDataImpl(RandomGenerator) - Constructor for class org.apache.commons.math.random.RandomDataImpl
  Construct a RandomDataImpl using the supplied `RandomGenerator` as the source of (non-secure) random data.
randomGenerator - Static variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  Static random number generator shared by GA implementation classes.
randomGenerator - Variable in class org.apache.commons.math.random.RandomAdaptor
  Wrapped randomGenerator instance
RandomGenerator - Interface in org.apache.commons.math.random
  Interface extracted from `java.util.Random`.
RandomKey<T> - Class in org.apache.commons.math.genetics
  Random Key chromosome is used for permutation representation.
RandomKey(List<Double>) - Constructor for class org.apache.commons.math.genetics.RandomKey
  Constructor.
RandomKey(Double[]) - Constructor for class org.apache.commons.math.genetics.RandomKey
  Constructor.
RandomKeyMutation - Class in org.apache.commons.math.genetics
  Mutation operator for `RandomKey`s.
RandomKeyMutation() - Constructor for class org.apache.commons.math.genetics.RandomKeyMutation
randomPermutation(int) - Static method in class org.apache.commons.math.genetics.RandomKey
  Generates a representation corresponding to a random permutation of length l which can be passed to the RandomKey constructor.
RandomVectorGenerator - Interface in org.apache.commons.math.random
  This interface represents a random generator for whole vectors.
rank - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Rank of the jacobian matrix.
rank - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Rank of the jacobian matrix.
rank - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Rank of the covariance matrix.
rank(double[]) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Rank `data` using the natural ordering on Doubles, with NaN values handled according to `nanStrategy` and ties resolved using `tiesStrategy.`
rank(double[]) - Method in interface org.apache.commons.math.stat.ranking.RankingAlgorithm
  Performs a rank transformation on the input data, returning an array of ranks.
rankCorrelation - Variable in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Rank correlation
rankingAlgorithm - Variable in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Ranking algorithm
RankingAlgorithm - Interface in org.apache.commons.math.stat.ranking
  Interface representing a rank transformation.
rankTransform(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Applies rank transform to each of the columns of `matrix` using the current `rankingAlgorithm`
rDiag - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
  The diagonal elements of R.
rDiag - Variable in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  The diagonal elements of R.
readArray(ObjectInput, double[]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Read an array.
readArray(ObjectInput, double[][]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Read an array.
readBaseExternal(ObjectInput) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Read the base state of the instance.
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Read the instance from an input channel.
readExternal(ObjectInput) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
readObject(ObjectInputStream) - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
  Deserialize the instance.
readObject(ObjectInputStream) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Deserialize the instance.
readObject(ObjectInputStream) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Deserialize the instance.
readObject(ObjectInputStream) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Read a serialized object.
readObject(ObjectInputStream) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Read a serialized object.
readResolve() - Method in class org.apache.commons.math.complex.Complex
  Resolve the transient fields in a deserialized Complex Object.
readResolve() - Method in class org.apache.commons.math.complex.ComplexField
  Handle deserialization of the singleton.
readResolve() - Method in class org.apache.commons.math.fraction.BigFractionField
  Handle deserialization of the singleton.
readResolve() - Method in class org.apache.commons.math.fraction.FractionField
  Handle deserialization of the singleton.
readResolve() - Method in class org.apache.commons.math.ode.sampling.DummyStepHandler
  Handle deserialization of the singleton.
readResolve() - Method in class org.apache.commons.math.util.BigRealField
  Handle deserialization of the singleton.
real - Variable in class org.apache.commons.math.complex.Complex
  The real part.
RealConvergenceChecker - Interface in org.apache.commons.math.optimization
  This interface specifies how to check if an `optimization algorithm` has converged.
realEigenvalues - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Real part of the realEigenvalues.
realEigenvalues - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Real part of the realEigenvalues.
realFormat - Variable in class org.apache.commons.math.complex.ComplexFormat
  The format used for the real part.
RealMatrix - Interface in org.apache.commons.math.linear
  Interface defining a real-valued matrix with basic algebraic operations.
RealMatrixChangingVisitor - Interface in org.apache.commons.math.linear
  Interface defining a visitor for matrix entries.
RealMatrixImpl - Class in org.apache.commons.math.linear
  Deprecated. as of 2.0 replaced by `Array2DRowRealMatrix`
RealMatrixImpl() - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Creates a matrix with no data
RealMatrixImpl(int, int) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Create a new RealMatrix with the supplied row and column dimensions.
RealMatrixImpl(double[][]) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Create a new RealMatrix using the input array as the underlying data array.
RealMatrixImpl(double[][], boolean) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Create a new RealMatrix using the input array as the underlying data array.
RealMatrixImpl(double[]) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Create a new (column) RealMatrix using `v` as the data for the unique column of the `v.length x 1` matrix created.
RealMatrixPreservingVisitor - Interface in org.apache.commons.math.linear
  Interface defining a visitor for matrix entries.
RealPointValuePair - Class in org.apache.commons.math.optimization
  This class holds a point and the value of an objective function at this point.
RealPointValuePair(double[], double) - Constructor for class org.apache.commons.math.optimization.RealPointValuePair
  Build a point/objective function value pair.
RealPointValuePair(double[], double, boolean) - Constructor for class org.apache.commons.math.optimization.RealPointValuePair
  Build a point/objective function value pair.
RealTransformer - Interface in org.apache.commons.math.transform
  Interface for one-dimensional data sets transformations producing real results.
RealVector - Interface in org.apache.commons.math.linear
  Interface defining a real-valued vector with basic algebraic operations.
RealVector.Entry - Class in org.apache.commons.math.linear
  Class representing a modifiable entry in the vector.
RealVector.Entry() - Constructor for class org.apache.commons.math.linear.RealVector.Entry
RealVectorFormat - Class in org.apache.commons.math.linear
  Formats a vector in components list format "{v0; v1; ...; vk-1}".
RealVectorFormat() - Constructor for class org.apache.commons.math.linear.RealVectorFormat
  Create an instance with default settings.
RealVectorFormat(NumberFormat) - Constructor for class org.apache.commons.math.linear.RealVectorFormat
  Create an instance with a custom number format for components.
RealVectorFormat(String, String, String) - Constructor for class org.apache.commons.math.linear.RealVectorFormat
  Create an instance with custom prefix, suffix and separator.
RealVectorFormat(String, String, String, NumberFormat) - Constructor for class org.apache.commons.math.linear.RealVectorFormat
  Create an instance with custom prefix, suffix, separator and format for components.
reciprocal() - Method in class org.apache.commons.math.fraction.BigFraction
  Return the multiplicative inverse of this fraction.
reciprocal() - Method in class org.apache.commons.math.fraction.Fraction
  Return the multiplicative inverse of this fraction.
recodeNaNs(NaturalRanking.IntDoublePair[], double) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Recodes NaN values to the given value.
recomputeZ() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Recompute the normalization factor.
reduce() - Method in class org.apache.commons.math.fraction.BigFraction
  Reduce this `BigFraction` to its lowest terms.
referenceCount - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Reference modification count.
referenceCount - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Reference modification count.
referenceTime - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Reference time for all arrays.
regularizedBeta(double, double, double) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedBeta(double, double, double, double) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedBeta(double, double, double, int) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedBeta(double, double, double, double, int) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedGammaP(double, double) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function P(a, x).
regularizedGammaP(double, double, double, int) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function P(a, x).
regularizedGammaQ(double, double) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
regularizedGammaQ(double, double, double, int) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
reinitialize(AbstractIntegrator, double[], double[][], boolean) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Reinitialize the instance
reinitialize(AbstractIntegrator, double[], double[][], boolean) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Reinitialize the instance
reinitialize(AbstractIntegrator, double[], double[][], boolean) - Method in class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
  Reinitialize the instance
reinitialize(double[], boolean) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Reinitialize the instance
reinitialize(double[], boolean) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Reinitialize the instance.
reinitialize(double, double, double[], Array2DRowRealMatrix) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Reinitialize the instance.
reinitializeBegin(double, double[]) - Method in class org.apache.commons.math.ode.events.EventState
  Reinitialize the beginning of the step.
relationship - Variable in class org.apache.commons.math.optimization.linear.LinearConstraint
  Relationship between left and right hand sides (=, <=, >=).
Relationship - Enum in org.apache.commons.math.optimization.linear
  Types of relationships between two cells in a Solver `LinearConstraint`.
Relationship(String) - Constructor for enum org.apache.commons.math.optimization.linear.Relationship
  Simple constructor.
relativeAccuracy - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
  Maximum relative error.
relativeThreshold - Variable in class org.apache.commons.math.optimization.SimpleRealPointChecker
  Relative tolerance threshold.
relativeThreshold - Variable in class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Relative tolerance threshold.
relativeThreshold - Variable in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Relative tolerance threshold.
relativeThreshold - Variable in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Relative tolerance threshold.
remove() - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
remove() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
remove(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Remove the value associated with a key.
remove(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Remove the value associated with a key.
REMOVED - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Status indicator for removed table entries.
REMOVED - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Status indicator for removed table entries.
removeData(double, double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Removes the observation (x,y) from the regression data set.
removeData(double[][]) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Removes observations represented by the elements in `data`.
removeMostRecentValue() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Removes the most recent value from the dataset.
removeNaNs(NaturalRanking.IntDoublePair[]) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Returns an array that is a copy of the input array with IntDoublePairs having NaN values removed.
removeTransformer(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
  Removes a Class to Transformer Mapping in the Map.
replaceMostRecentValue(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Replaces the most recently stored value with the given value.
replaceWorstPoint(RealPointValuePair, Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Replace the worst point of the simplex by a new point.
REPLAY_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Replay data from valuesFilePath.
representation - Variable in class org.apache.commons.math.genetics.AbstractListChromosome
  List representing the chromosome
requiresDenseOutput() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Check if one of the step handlers requires dense output.
requiresDenseOutput() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Determines whether this handler needs dense output.
requiresDenseOutput() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Determines whether this handler needs dense output.
requiresDenseOutput() - Method in interface org.apache.commons.math.ode.jacobians.StepHandlerWithJacobians
  Determines whether this handler needs dense output.
requiresDenseOutput() - Method in class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
  Determines whether this handler needs dense output.
requiresDenseOutput() - Method in class org.apache.commons.math.ode.sampling.DummyStepHandler
  Determines whether this handler needs dense output.
requiresDenseOutput() - Method in interface org.apache.commons.math.ode.sampling.StepHandler
  Determines whether this handler needs dense output.
requiresDenseOutput() - Method in class org.apache.commons.math.ode.sampling.StepNormalizer
  Determines whether this handler needs dense output.
rescale(double[], double[], double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Update scaling array.
rescale(double) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Rescale the instance.
reSeed(long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the random number generator with the supplied seed.
reSeed() - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the random number generator with the current time in milliseconds.
reSeedSecure() - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the secure random number generator with the current time in milliseconds.
reSeedSecure(long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the secure random number generator with the supplied seed.
reset() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Reset "illumination" and "sampleIndex".
reset() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Reset the step handler.
reset(double, double[]) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Let the event handlers reset the state if they want.
reset(double, double[]) - Method in class org.apache.commons.math.ode.events.EventState
  Let the event handler reset the state if it wants.
reset() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
  Reset the step handler.
reset() - Method in interface org.apache.commons.math.ode.jacobians.StepHandlerWithJacobians
  Reset the step handler.
reset() - Method in class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
  Reset the step handler.
reset() - Method in class org.apache.commons.math.ode.sampling.DummyStepHandler
  Reset the step handler.
reset() - Method in interface org.apache.commons.math.ode.sampling.StepHandler
  Reset the step handler.
reset() - Method in class org.apache.commons.math.ode.sampling.StepNormalizer
  Reset the step handler.
RESET_DERIVATIVES - Static variable in interface org.apache.commons.math.ode.events.EventHandler
  Reset derivatives indicator.
RESET_DERIVATIVES - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Reset derivatives indicator.
RESET_STATE - Static variable in interface org.apache.commons.math.ode.events.EventHandler
  Reset state indicator.
RESET_STATE - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Reset state indicator.
resetAbsoluteAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Reset the absolute accuracy to the default.
resetAbsoluteAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Reset the absolute accuracy to the default.
resetAbsoluteAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Reset the absolute accuracy to the default.
resetEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Reset the number of evaluations to zero.
resetFunctionValueAccuracy() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Reset the actual function accuracy to the default.
resetFunctionValueAccuracy() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Reset the actual function accuracy to the default.
resetInternalState() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Reset internal state to dummy values.
resetMaximalIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Reset the upper limit for the number of iterations to the default.
resetMaximalIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Reset the upper limit for the number of iterations to the default.
resetMaximalIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Reset the upper limit for the number of iterations to the default.
resetMinimalIterationCount() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
  Reset the lower limit for the number of iterations to the default.
resetMinimalIterationCount() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Reset the lower limit for the number of iterations to the default.
resetRelativeAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Reset the relative accuracy to the default.
resetRelativeAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Reset the relative accuracy to the default.
resetRelativeAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Reset the relative accuracy to the default.
resetReplayFile() - Method in class org.apache.commons.math.random.ValueServer
  Resets REPLAY_MODE file pointer to the beginning of the `valuesFileURL`.
resetState(double, double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
  Reset the state prior to continue the integration.
resetState(double, double[]) - Method in interface org.apache.commons.math.ode.events.EventHandler
  Reset the state prior to continue the integration.
resetState(double, double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Reset the state prior to continue the integration.
resetState(double, double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  Reset the state prior to continue the integration.
resetTables(int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Reallocate the internal tables.
residuals - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Residuals array.
residuals - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Current residuals.
residualsWeights - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Weight for the least squares cost computation.
ResizableDoubleArray - Class in org.apache.commons.math.util
  A variable length `DoubleArray` implementation that automatically handles expanding and contracting its internal storage array as elements are added and removed.
ResizableDoubleArray() - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with default properties.
ResizableDoubleArray(int) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified initial capacity.
ResizableDoubleArray(int, float) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified initial capacity and expansion factor.
ResizableDoubleArray(int, float, float) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified initialCapacity, expansionFactor, and contractionCriteria.
ResizableDoubleArray(int, float, float, int) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified properties.
ResizableDoubleArray(ResizableDoubleArray) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Copy constructor.
RESIZE_MULTIPLIER - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Multiplier for size growth when map fills up.
RESIZE_MULTIPLIER - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Multiplier for size growth when map fills up.
resolveTie(double[], List<Integer>) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Resolve a sequence of ties, using the configured `TiesStrategy`.
restoreNaNs(double[], List<Integer>) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
  Set `ranks[i] = Double.NaN` for each i in `nanPositions.`
restrictToNonNegative - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Whether to restrict the variables to non-negative values.
result - Variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  the last computed integral
result - Variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  The last computed root.
result - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  The last computed root.
resultComputed - Variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  indicates whether an integral has been computed
resultComputed - Variable in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Indicates where a root has been computed.
resultComputed - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Indicates where a root has been computed.
revert() - Method in class org.apache.commons.math.geometry.Rotation
  Revert a rotation.
rho - Variable in class org.apache.commons.math.optimization.direct.NelderMead
  Reflection coefficient.
RiddersSolver - Class in org.apache.commons.math.analysis.solvers
  Implements the Ridders' Method for root finding of real univariate functions.
RiddersSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.RiddersSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `RiddersSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
RiddersSolver() - Constructor for class org.apache.commons.math.analysis.solvers.RiddersSolver
  Construct a solver.
RINT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.rint` method wrapped as a `ComposableFunction`.
robustnessIters - Variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  The number of robustness iterations parameter: this many robustness iterations are done.
RombergIntegrator - Class in org.apache.commons.math.analysis.integration
  Implements the Romberg Algorithm for integration of real univariate functions.
RombergIntegrator(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.integration.RombergIntegrator
  Deprecated. as of 2.0 the integrand function is passed as an argument to the `RombergIntegrator.integrate(UnivariateRealFunction, double, double)`method.
RombergIntegrator() - Constructor for class org.apache.commons.math.analysis.integration.RombergIntegrator
  Construct an integrator.
root - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Permutated Cholesky root of the covariance matrix.
roots - Variable in class org.apache.commons.math.transform.FastFourierTransformer
  roots of unity
Rotation - Class in org.apache.commons.math.geometry
  This class implements rotations in a three-dimensional space.
Rotation(double, double, double, double, boolean) - Constructor for class org.apache.commons.math.geometry.Rotation
  Build a rotation from the quaternion coordinates.
Rotation(Vector3D, double) - Constructor for class org.apache.commons.math.geometry.Rotation
  Build a rotation from an axis and an angle.
Rotation(double[][], double) - Constructor for class org.apache.commons.math.geometry.Rotation
  Build a rotation from a 3X3 matrix.
Rotation(Vector3D, Vector3D, Vector3D, Vector3D) - Constructor for class org.apache.commons.math.geometry.Rotation
  Build the rotation that transforms a pair of vector into another pair.
Rotation(Vector3D, Vector3D) - Constructor for class org.apache.commons.math.geometry.Rotation
  Build one of the rotations that transform one vector into another one.
Rotation(RotationOrder, double, double, double) - Constructor for class org.apache.commons.math.geometry.Rotation
  Build a rotation from three Cardan or Euler elementary rotations.
RotationOrder - Class in org.apache.commons.math.geometry
  This class is a utility representing a rotation order specification for Cardan or Euler angles specification.
RotationOrder(String, Vector3D, Vector3D, Vector3D) - Constructor for class org.apache.commons.math.geometry.RotationOrder
  Private constructor.
round(double, int) - Static method in class org.apache.commons.math.util.MathUtils
  Round the given value to the specified number of decimal places.
round(double, int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Round the given value to the specified number of decimal places.
round(float, int) - Static method in class org.apache.commons.math.util.MathUtils
  Round the given value to the specified number of decimal places.
round(float, int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Round the given value to the specified number of decimal places.
roundingMode - Variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Rounding mode for divisions
roundingMode - Variable in class org.apache.commons.math.util.BigReal
  Rounding mode for divisions.
roundUnscaled(double, double, int) - Static method in class org.apache.commons.math.util.MathUtils
  Round the given non-negative, value to the "nearest" integer.
rows - Variable in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Number of rows of the jacobian matrix.
rows - Variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Number of rows of the matrix.
rows - Variable in class org.apache.commons.math.linear.BlockRealMatrix
  Number of rows of the matrix.
rows - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
  Number of rows of the matrix.
rows - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
  row dimension
rows - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Number of rows of the jacobian matrix.
RungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the common part of all fixed step Runge-Kutta integrators for Ordinary Differential Equations.
RungeKuttaIntegrator(String, double[], double[][], double[], RungeKuttaStepInterpolator, double) - Constructor for class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Simple constructor.
RungeKuttaStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class represents an interpolator over the last step during an ODE integration for Runge-Kutta and embedded Runge-Kutta integrators.
RungeKuttaStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
  Simple constructor.
RungeKuttaStepInterpolator(RungeKuttaStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
  Copy constructor.

## S

s - Variable in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Intermediate result.
S_LIMIT - Static variable in class org.apache.commons.math.special.Gamma
  S limit.
SaddlePointExpansion - Class in org.apache.commons.math.distribution
  Utility class used by various distributions to accurately compute their respective probability mass functions.
SaddlePointExpansion() - Constructor for class org.apache.commons.math.distribution.SaddlePointExpansion
  Default constructor.
SAFE_MIN - Static variable in class org.apache.commons.math.util.MathUtils
  Safe minimum, such that 1 / SAFE_MIN does not overflow.
safety - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Safety factor for stepsize control.
safety - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Safety factor for stepsize control.
sample() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Get the sample illuminating the element the most.
sample(UnivariateRealFunction, double, double, int) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Sample the given univariate real function on the given interval.
samples - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
  Sample data.
sampleSize - Variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  The sample size.
sampleStats - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Sample statistics
sanityChecks(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Perform some sanity checks on the integration parameters.
sanityChecks(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Perform some sanity checks on the integration parameters.
scalAbsoluteTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Allowed absolute scalar error.
scalarAdd(T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the result of adding d to each entry of this.
scalarAdd(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result of adding d to each entry of this.
scalarAdd(T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(T) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of adding d to each entry of this.
scalarMultiply(double) - Method in class org.apache.commons.math.geometry.Vector3D
  Multiply the instance by a scalar
scalarMultiply(T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the result multiplying each entry of this by d.
scalarMultiply(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the result of multiplying each entry of this by `d`
scalarMultiply(T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(T) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result multiplying each entry of this by d.
scalb(double, int) - Static method in class org.apache.commons.math.util.MathUtils
  Scale a number by 2scaleFactor.
scale - Variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
  The scale of this distribution.
scale - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
  The scale parameter.
scale - Variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. BigDecimal scale
scale - Variable in class org.apache.commons.math.optimization.LeastSquaresConverter
  Optional scaling matrix (weight and correlations) for the residuals.
scale - Variable in class org.apache.commons.math.util.BigReal
  BigDecimal scale
scaleArray(double[], double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Multiply every component in the given real array by the given real number.
scaleArray(Complex[], double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Multiply every component in the given complex array by the given real number.
scaled - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  First scaled derivative (h y').
scaled - Variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Current scaled first derivative.
scaled - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  First scaled derivative.
scalingH - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Step size used in the first scaled derivative and Nordsieck vector.
scalRelativeTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Allowed relative scalar error.
searchDirection - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.LineSearchFunction
  Search direction.
searchForFitnessUpdate(Population) - Method in class org.apache.commons.math.genetics.Chromosome
  Searches the population for a chromosome representing the same solution, and if it finds one, updates the fitness to its value.
searchIndex(double, double[]) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
SecantSolver - Class in org.apache.commons.math.analysis.solvers
  Implements a modified version of the secant method for approximating a zero of a real univariate function.
SecantSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.SecantSolver
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `SecantSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
SecantSolver() - Constructor for class org.apache.commons.math.analysis.solvers.SecantSolver
  Construct a solver.
second - Variable in class org.apache.commons.math.genetics.ChromosomePair
  the second chromosome in the pair.
secondary - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
  Secondary diagonal.
secondary - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Secondary diagonal of the tridiagonal matrix.
secondary - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
  Secondary diagonal.
SecondMoment - Class in org.apache.commons.math.stat.descriptive.moment
  Computes a statistic related to the Second Central Moment.
SecondMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Create a SecondMoment instance
SecondMoment(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Copy constructor, creates a new `SecondMoment` identical to the `original`
secondMoment - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  SecondMoment is used to compute the mean and variance
SecondOrderDifferentialEquations - Interface in org.apache.commons.math.ode
  This interface represents a second order differential equations set.
SecondOrderIntegrator - Interface in org.apache.commons.math.ode
  This interface represents a second order integrator for differential equations.
secRand - Variable in class org.apache.commons.math.random.RandomDataImpl
  underlying secure random number generator
select(Population) - Method in interface org.apache.commons.math.genetics.SelectionPolicy
  Select two chromosomes from the population.
select(Population) - Method in class org.apache.commons.math.genetics.TournamentSelection
  Select two chromosomes from the population.
selectionPolicy - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
  the selection policy used by the algorithm.
SelectionPolicy - Interface in org.apache.commons.math.genetics
  Algorithm used to select a chromosome pair from a population.
SemiVariance - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the semivariance of a set of values with respect to a given cutoff value.
SemiVariance() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Constructs a SemiVariance with default (true) `biasCorrected` property and default (Downside) `varianceDirection` property.
SemiVariance(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Constructs a SemiVariance with the specified `biasCorrected` property and default (Downside) `varianceDirection` property.
SemiVariance(SemiVariance.Direction) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Constructs a SemiVariance with the specified `Direction` property and default (true) `biasCorrected` property
SemiVariance(boolean, SemiVariance.Direction) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Constructs a SemiVariance with the specified `isBiasCorrected` property and the specified `Direction` property.
SemiVariance(SemiVariance) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Copy constructor, creates a new `SemiVariance` identical to the `original`
SemiVariance.Direction - Enum in org.apache.commons.math.stat.descriptive.moment
  The direction of the semivariance - either upside or downside.
SemiVariance.Direction(boolean) - Constructor for enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
  Create a Direction with the given value.
separator - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  Separator.
separator - Variable in class org.apache.commons.math.linear.RealVectorFormat
  Separator.
sequence - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  step size sequence.
serializeRealMatrix(RealMatrix, ObjectOutputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Serialize a `RealMatrix`.
serializeRealVector(RealVector, ObjectOutputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Serialize a `RealVector`.
serialVersionUID - Static variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
  serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.analysis.interpolation.NevilleInterpolator
  serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Serialization identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.solvers.BrentSolver
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.ArgumentOutsideDomainException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.complex.Complex
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.complex.ComplexField
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.complex.ComplexFormat
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.ConvergenceException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.DimensionMismatchException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractDistribution
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.BetaDistributionImpl
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.FDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.GammaDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.PascalDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.TDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.DuplicateSampleAbscissaException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.estimation.EstimationException
  Deprecated. Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.fraction.AbstractFormat
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.fraction.BigFraction
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.fraction.BigFractionField
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.fraction.BigFractionFormat
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.fraction.Fraction
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.fraction.FractionConversionException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.fraction.FractionField
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.fraction.FractionFormat
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.fraction.ProperBigFractionFormat
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.fraction.ProperFractionFormat
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.FunctionEvaluationException
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.genetics.InvalidRepresentationException
  Serialization version id
serialVersionUID - Static variable in exception org.apache.commons.math.geometry.CardanEulerSingularityException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.geometry.NotARotationMatrixException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.geometry.Rotation
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.geometry.Vector3D
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.geometry.Vector3DFormat
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.ArrayFieldVector
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.linear.ArrayRealVector
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Serialization id
serialVersionUID - Static variable in class org.apache.commons.math.linear.BlockFieldMatrix
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.BlockRealMatrix
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.linear.InvalidMatrixException
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.linear.MatrixIndexException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.linear.MatrixVisitorException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.linear.NonSquareMatrixException
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.linear.NotPositiveDefiniteMatrixException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.linear.NotSymmetricMatrixException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.OpenMapRealMatrix
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.linear.OpenMapRealVector
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.RealVectorFormat
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.linear.SingularMatrixException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.linear.SparseFieldMatrix
  Serial id
serialVersionUID - Static variable in class org.apache.commons.math.linear.SparseFieldVector
  Serial version id
serialVersionUID - Static variable in exception org.apache.commons.math.MathConfigurationException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.MathException
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.MathRuntimeException
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.MaxEvaluationsExceededException
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.MaxIterationsExceededException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.ode.ContinuousOutputModel
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.ode.DerivativeException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.ode.events.EventException
  Serialization UID.
serialVersionUID - Static variable in exception org.apache.commons.math.ode.IntegratorException
  Serializable version identifier
serialVersionUID - Static variable in exception org.apache.commons.math.ode.MultistepIntegrator.InitializationCompletedMarkerException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Serializable version id.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.linear.LinearConstraint
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.optimization.linear.NoFeasibleSolutionException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.optimization.linear.UnboundedSolutionException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Serializable version identifier.
serialVersionUID - Static variable in exception org.apache.commons.math.optimization.OptimizationException
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.RealPointValuePair
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.optimization.VectorialPointValuePair
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.random.JDKRandomGenerator
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.random.MersenneTwister
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.random.RandomAdaptor
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.random.RandomDataImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.random.UniformRandomGenerator
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.stat.clustering.Cluster
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
  The serialization version of this class
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Mean
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Max
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Median
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Min
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Serialization id
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.Product
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.Sum
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.Frequency.NaturalComparator
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.Frequency
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.regression.SimpleRegression
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
  Serializable version id.
serialVersionUID - Static variable in class org.apache.commons.math.transform.FastFourierTransformer
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.util.BigReal
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.util.BigRealField
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.CompositeFormat
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.util.DefaultTransformer
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Serializable version identifier.
serialVersionUID - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.TransformerMap
  Serializable version identifier
set(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Set all elements to a single value.
set(int, ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Set a set of consecutive elements.
set(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Set all elements to a single value.
set(int, ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Set a set of consecutive elements.
set(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Set all elements to a single value.
set(T) - Method in interface org.apache.commons.math.linear.FieldVector
  Set all elements to a single value.
set(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Set all elements to a single value.
set(double) - Method in interface org.apache.commons.math.linear.RealVector
  Set all elements to a single value.
set(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Set all elements to a single value.
set(Complex, int...) - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
  Set a matrix element.
SET_QUANTILE_METHOD_NAME - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Name of the setQuantile method.
setAbsoluteAccuracy(double) - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Set the absolute accuracy.
setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Set the absolute accuracy.
setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Set the absolute accuracy.
setAlpha(double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
  Deprecated. as of 2.1
setAlpha(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setAlpha(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Deprecated. as of v2.1
setAlpha(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setAlphaInternal(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Modify the shape parameter, alpha.
setArity(int) - Method in class org.apache.commons.math.genetics.TournamentSelection
  Sets the arity (number of chromosomes drawn to the tournament).
setBeta(double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
  Deprecated. as of 2.1
setBeta(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setBeta(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Deprecated. as of v2.1
setBeta(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setBetaInternal(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Modify the scale parameter, beta.
setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Sets the biasCorrected property.
setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
setBound(boolean) - Method in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Set the bound flag of the parameter
setBrightnessExponent(int) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Set the brightness exponent.
setChiSquareTest(TTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Set the (singleton) TTest instance.
setChiSquareTest(ChiSquareTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Set the (singleton) ChiSquareTest instance.
setChromosomes(List<Chromosome>) - Method in class org.apache.commons.math.genetics.ListPopulation
  Sets the list of chromosomes.
setColumn(int, T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumn(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumn(int, T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumn(int, double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumn(int, T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumn(int, double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnMatrix(int, RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Sets the entries in column number `column` as a column matrix.
setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Sets the entries in column number `column` as a vector.
setColumnVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Sets the entries in column number `column` as a vector.
setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in column number `column` as a vector.
setColumnVector(int, RealVector) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in column number `column` as a vector.
setColumnVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Sets the entries in column number `column` as a vector.
setColumnVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
  Sets the entries in column number `column` as a vector.
setContractionCriteria(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the contraction criteria for this ExpandContractDoubleArray.
setConvergence(double) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Set the convergence criterion threshold.
setConvergenceChecker(RealConvergenceChecker) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Set the convergence checker.
setConvergenceChecker(VectorialConvergenceChecker) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Set the convergence checker.
setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Set the convergence checker.
setConvergenceChecker(VectorialConvergenceChecker) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Set the convergence checker.
setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Set the convergence checker.
setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Set the convergence checker.
setConvergenceChecker(VectorialConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Set the convergence checker.
setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Set the convergence checker.
setConvergenceChecker(RealConvergenceChecker) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Set the convergence checker.
setCostRelativeTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Set the desired relative error in the sum of squares.
setCostRelativeTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Set the desired relative error in the sum of squares.
setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
  Deprecated. as of v2.1
setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.TDistribution
  Deprecated. as of v2.1
setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Modify the degrees of freedom.
setDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Modify the degrees of freedom.
setDenominatorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
  Deprecated. as of v2.1
setDenominatorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setDenominatorDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Modify the denominator degrees of freedom.
setDenominatorFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.AbstractFormat
  Modify the denominator format.
setDistribution(ChiSquaredDistribution) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Modify the distribution used to compute inference statistics.
setDistribution(TDistribution) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Modify the distribution used to compute inference statistics.
setDistribution(TDistribution) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Modify the distribution used to compute inference statistics.
setElement(int, double) - Method in interface org.apache.commons.math.util.DoubleArray
  Sets the element at the specified index.
setElement(int, double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the element at the specified index.
setElitismRate(double) - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
  Sets the elitism rate, i.e.
setEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Set the entry in the specified row and column.
setEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Set the entry in the specified row and column.
setEntry(int, T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Set a single element.
setEntry(int, double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Set a single element.
setEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Set the entry in the specified row and column.
setEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Set the entry in the specified row and column.
setEntry(int, T) - Method in interface org.apache.commons.math.linear.FieldVector
  Set a single element.
setEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Set the entry in the specified row and column.
setEntry(int, double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Set a single element.
setEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Set the entry in the specified row and column.
setEntry(int, double) - Method in interface org.apache.commons.math.linear.RealVector
  Set a single element.
setEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
  Set the entry in the specified row and column.
setEntry(int, T) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Set a single element.
setEntry(int, int, double) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Set an entry of the tableau.
setEquations(FirstOrderDifferentialEquations) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Set the differential equations.
setEstimate(double) - Method in class org.apache.commons.math.estimation.EstimatedParameter
  Deprecated. Set a new estimated value for the parameter.
setExpansionFactor(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the expansionFactor.
setExpansionMode(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the `expansionMode`.
setExponent(double) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
  Deprecated. as of v2.1
setExponent(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setExponentInternal(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Set the exponent characterising the distribution.
setFunctionValueAccuracy(double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Set the function value accuracy.
setFunctionValueAccuracy(double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Set the function value accuracy.
setGamma(GammaDistribution) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setGammaInternal(GammaDistribution) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Modify the underlying gamma distribution.
setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the geometric mean.
setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the geometric mean.
setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the geometric mean.
setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the geometric mean.
setGeometricMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the gemoetric mean.
setIgnored(boolean) - Method in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Set the ignore flag to the specified value Setting the ignore flag to true allow to reject wrong measurements, which sometimes can be detected only rather late.
setImaginaryCharacter(String) - Method in class org.apache.commons.math.complex.ComplexFormat
  Modify the imaginaryCharacter.
setImaginaryFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
  Modify the imaginaryFormat.
setImpl(StorelessUnivariateStatistic[], StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets statistics implementations.
setIndex(int) - Method in class org.apache.commons.math.linear.RealVector.Entry
  Set the index of the entry.
setInitialCapacity(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the initial capacity.
setInitialStep(double) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Set the initial step used to bracket the optimum in line search.
setInitialStepBoundFactor(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Set the positive input variable used in determining the initial step bound.
setInitialStepBoundFactor(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Set the positive input variable used in determining the initial step bound.
setInitialStepSize(double) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Set the initial step size.
setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
  Set the time of the interpolated point.
setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Set the time of the interpolated point.
setInterpolatedTime(double) - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
  Set the time of the interpolated point.
setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Set the time of the interpolated point.
setInterpolatedTime(double) - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
  Set the time of the interpolated point.
setInterpolationControl(boolean, int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Set the interpolation order control parameter.
setKurtosisImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the kurtosis.
setLineSearchSolver(UnivariateRealSolver) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Set the solver to use during line search.
setMaxCostEval(int) - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Set the maximal number of cost evaluations allowed.
setMaxEvaluations(int) - Method in class org.apache.commons.math.ode.AbstractIntegrator
  Set the maximal number of differential equations function evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
  Set the maximal number of differential equations function evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math.ode.ODEIntegrator
  Set the maximal number of differential equations function evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
  Set the maximal number of functions evaluations.
setMaxGrowth(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Set the maximal growth factor for stepsize control.
setMaxGrowth(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Set the maximal growth factor for stepsize control.
setMaximalIterationCount(int) - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Set the upper limit for the number of iterations.
setMaximalIterationCount(int) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Set the upper limit for the number of iterations.
setMaximalIterationCount(int) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Set the upper limit for the number of iterations.
setMaxImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the maximum.
setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Set the maximal number of iterations of the algorithm.
setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
  Set the maximal number of iterations of the algorithm.
setMean(double) - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
  Deprecated. as of v2.1
setMean(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setMean(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Deprecated. as of v2.1
setMean(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setMean(double) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Deprecated. as of v2.1
setMean(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the mean.
setMeanInternal(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Modify the mean.
setMeanInternal(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Modify the mean.
setMedian(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
  Deprecated. as of v2.1
setMedian(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setMedianInternal(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Modify the median.
setMicropshereElements(int) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
  Set the number of microsphere elements.
setMinimalIterationCount(int) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
  Set the lower limit for the number of iterations.
setMinimalIterationCount(int) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Set the lower limit for the number of iterations.
setMinImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the minimum.
setMinReduction(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Set the minimal reduction factor for stepsize control.
setMinReduction(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Set the minimal reduction factor for stepsize control.
setMode(int) - Method in class org.apache.commons.math.random.ValueServer
  Setter for property mode.
setMu(double) - Method in class org.apache.commons.math.random.ValueServer
  Setter for property mu.
setNormal(NormalDistribution) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setNormalAndMeanInternal(NormalDistribution, double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Set the Poisson mean for the distribution.
setNumberOfElements(int) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
  Deprecated. as of v2.1
setNumberOfElements(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setNumberOfElementsInternal(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
  Set the number of elements (e.g.
setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Deprecated. as of v2.1
setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.PascalDistribution
  Deprecated. as of v2.1
setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setNumberOfSuccessesInternal(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the number of successes.
setNumberOfSuccessesInternal(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Change the number of successes for this distribution.
setNumberOfTrials(int) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Deprecated. as of v2.1
setNumberOfTrials(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setNumberOfTrialsInternal(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Change the number of trials for this distribution.
setNumElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  This function allows you to control the number of elements contained in this array, and can be used to "throw out" the last n values in an array.
setNumeratorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
  Deprecated. as of v2.1
setNumeratorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setNumeratorDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Modify the numerator degrees of freedom.
setNumeratorFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.AbstractFormat
  Modify the numerator format.
setOneWayAnova(OneWayAnova) - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Set the (singleton) OneWayAnova instance
setOrderControl(int, double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Set the order control parameters.
setOrthoTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Set the desired max cosine on the orthogonality.
setOrthoTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Set the desired max cosine on the orthogonality.
setParameter(int, double) - Method in interface org.apache.commons.math.ode.jacobians.ParameterizedODE
  Set a parameter.
setParRelativeTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Set the desired relative error in the approximate solution parameters.
setParRelativeTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Set the desired relative error in the approximate solution parameters.
setPercentileImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation to be used by `DescriptiveStatistics.getPercentile(double)`.
setPopulationLimit(int) - Method in class org.apache.commons.math.genetics.ListPopulation
  Sets the maximal population size.
setPopulationSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Deprecated. as of v2.1
setPopulationSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setPopulationSizeInternal(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the population size.
setPreconditioner(Preconditioner) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Set the preconditioner.
setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Deprecated. as of v2.1
setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.PascalDistribution
  Deprecated. as of v2.1
setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setProbabilityOfSuccessInternal(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Change the probability of success for this distribution.
setProbabilityOfSuccessInternal(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
  Change the probability of success for this distribution.
setQuantile(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Sets the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
setRandomGenerator(RandomGenerator) - Static method in class org.apache.commons.math.genetics.GeneticAlgorithm
  Set the (static) random generator.
setRealFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
  Modify the realFormat.
setRelativeAccuracy(double) - Method in interface org.apache.commons.math.ConvergingAlgorithm
  Set the relative accuracy.
setRelativeAccuracy(double) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
  Set the relative accuracy.
setRelativeAccuracy(double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Set the relative accuracy.
setResult(double, int) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Convenience function for implementations.
setResult(double, int) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Convenience function for implementations.
setResult(double, double, int) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Convenience function for implementations.
setResult(double, double, int) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
  Convenience function for implementations.
setRoundingMode(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Sets the rounding mode for decimal divisions.
setRoundingMode(RoundingMode) - Method in class org.apache.commons.math.util.BigReal
  Sets the rounding mode for decimal divisions.
setRow(int, T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRow(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Sets the entries in row number `row` as a row matrix.
setRow(int, T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRow(int, double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in row number `row` as a row matrix.
setRow(int, T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRow(int, double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Sets the entries in row number `row` as a row matrix.
setRowMatrix(int, RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Sets the entries in row number `row` as a row matrix.
setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Sets the entries in row number `row` as a vector.
setRowVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Sets the entries in row number `row` as a vector.
setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Sets the entries in row number `row` as a vector.
setRowVector(int, RealVector) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Sets the entries in row number `row` as a vector.
setRowVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Sets the entries in row number `row` as a vector.
setRowVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
  Sets the entries in row number `row` as a vector.
setSafety(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Set the safety factor for stepsize control.
setSafety(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Set the safety factor for stepsize control.
setSampleSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Deprecated. as of v2.1
setSampleSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setSampleSizeInternal(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the sample size.
setScale(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
  Deprecated. as of v2.1
setScale(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setScale(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
  Deprecated. as of v2.1
setScale(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setScale(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Sets the scale for division operations.
setScale(int) - Method in class org.apache.commons.math.util.BigReal
  Sets the scale for division operations.
setScaleInternal(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Modify the scale parameter.
setScaleInternal(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Modify the scale parameter.
setSecureAlgorithm(String, String) - Method in class org.apache.commons.math.random.RandomDataImpl
  Sets the PRNG algorithm for the underlying SecureRandom instance using the Security Provider API.
setSeed(int) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Sets the seed of the underyling random number generator using an `int` seed.
setSeed(int[]) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Sets the seed of the underyling random number generator using an `int` array seed.
setSeed(long) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
  Sets the seed of the underyling random number generator using a `long` seed.
setSeed(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Sets the seed of the underyling random number generator using an `int` seed.
setSeed(int[]) - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Sets the seed of the underyling random number generator using an `int` array seed.
setSeed(long) - Method in class org.apache.commons.math.random.BitsStreamGenerator
  Sets the seed of the underyling random number generator using a `long` seed.
setSeed(int) - Method in class org.apache.commons.math.random.JDKRandomGenerator
  Sets the seed of the underyling random number generator using an `int` seed.
setSeed(int[]) - Method in class org.apache.commons.math.random.JDKRandomGenerator
  Sets the seed of the underyling random number generator using an `int` array seed.
setSeed(int) - Method in class org.apache.commons.math.random.MersenneTwister
  Reinitialize the generator as if just built with the given int seed.
setSeed(int[]) - Method in class org.apache.commons.math.random.MersenneTwister
  Reinitialize the generator as if just built with the given int array seed.
setSeed(long) - Method in class org.apache.commons.math.random.MersenneTwister
  Reinitialize the generator as if just built with the given long seed.
setSeed(int) - Method in class org.apache.commons.math.random.RandomAdaptor
  Sets the seed of the underyling random number generator using an `int` seed.
setSeed(int[]) - Method in class org.apache.commons.math.random.RandomAdaptor
  Sets the seed of the underyling random number generator using an `int` array seed.
setSeed(long) - Method in class org.apache.commons.math.random.RandomAdaptor
  Sets the seed of the underyling random number generator using a `long` seed.
setSeed(int) - Method in interface org.apache.commons.math.random.RandomGenerator
  Sets the seed of the underyling random number generator using an `int` seed.
setSeed(int[]) - Method in interface org.apache.commons.math.random.RandomGenerator
  Sets the seed of the underyling random number generator using an `int` array seed.
setSeed(long) - Method in interface org.apache.commons.math.random.RandomGenerator
  Sets the seed of the underyling random number generator using a `long` seed.
setShape(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
  Deprecated. as of v2.1
setShape(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setShapeInternal(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Modify the shape parameter.
setSigma(double) - Method in class org.apache.commons.math.random.ValueServer
  Setter for property sigma.
setSkewnessImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the skewness.
setStabilityCheck(boolean, int, int, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Set the stability check controls.
setStandardDeviation(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Deprecated. as of v2.1
setStandardDeviation(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Deprecated. as of 2.1 (class will become immutable in 3.0)
setStandardDeviationInternal(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Modify the standard deviation.
setStartConfiguration(double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Set start configuration for simplex.
setStartConfiguration(double[][]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Set start configuration for simplex.
setStarterIntegrator(FirstOrderIntegrator) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Set the starter integrator.
setSteadyStateThreshold(double) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Set the steady state detection threshold.
setStepsizeControl(double, double, double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Set the step size control factors.
setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(BigDecimal[][], int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(T[][], int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(double[][], int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Replace the submatrix starting at `row, column` using data in the input `subMatrix` array.
setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Set a set of consecutive elements.
setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Set a set of consecutive elements.
setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Set a set of consecutive elements.
setSubVector(int, T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Set a set of consecutive elements.
setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Set a set of consecutive elements.
setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Set a set of consecutive elements.
setSubVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Set a set of consecutive elements.
setSubVector(int, T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Set a set of consecutive elements.
setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Set a set of consecutive elements.
setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Set a set of consecutive elements.
setSubVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Set a set of consecutive elements.
setSubVector(int, double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Set a set of consecutive elements.
setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Set a set of consecutive elements.
setSubVector(int, T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Set a set of consecutive elements.
setSumImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the sum.
setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the Sum.
setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the Sum.
setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the Sum.
setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the Sum.
setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the sum of logs.
setSumsqImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the sum of squares.
setUnknownDistributionChiSquareTest(UnknownDistributionChiSquareTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
  Set the (singleton) UnknownDistributionChiSquareTest instance.
setup(UnivariateRealFunction) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  Checks to see if f is null, throwing IllegalArgumentException if so.
setValue(double) - Method in class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
  Set the value of the entry.
setValue(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
  Set the value of the entry.
setValue(double) - Method in class org.apache.commons.math.linear.RealVector.Entry
  Set the value of the entry.
setValuesFileURL(String) - Method in class org.apache.commons.math.random.ValueServer
  Sets the `valuesFileURL` using a string URL representation
setValuesFileURL(URL) - Method in class org.apache.commons.math.random.ValueServer
  Sets the `valuesFileURL`
setVarianceDirection(SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Sets the variance direction
setVarianceImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sets the implementation for the variance.
setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sets the implementation for the variance.
setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Sets the implementation for the variance.
setWholeFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
  Modify the whole format.
setWholeFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.ProperFractionFormat
  Modify the whole format.
setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  WindowSize controls the number of values which contribute to the reported statistics.
setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  WindowSize controls the number of values which contribute to the reported statistics.
SGN_MASK - Static variable in class org.apache.commons.math.util.MathUtils
  Offset to order signed double numbers lexicographically.
shape - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
  The shape parameter.
shift() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Shift one step forward.
shouldContract() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns true if the internal storage array has too many unused storage positions.
shouldGrowTable() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Check if tables should grow due to increased size.
shouldGrowTable() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Check if tables should grow due to increased size.
shuffle(int[], int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Uses a 2-cycle permutation shuffle to randomly re-order the last elements of list.
sigma - Variable in class org.apache.commons.math.optimization.direct.NelderMead
  Shrinkage coefficient.
sigma - Variable in class org.apache.commons.math.random.ValueServer
  Standard deviation for use with GAUSSIAN_MODE.
sign(byte) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for byte value `x`.
sign(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for double precision `x`.
sign(float) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for float value `x`.
sign(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for int value `x`.
sign(long) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for long value `x`.
sign(short) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for short value `x`.
SIGNUM - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.signum` method wrapped as a `ComposableFunction`.
SimpleEstimationProblem - Class in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
SimpleEstimationProblem() - Constructor for class org.apache.commons.math.estimation.SimpleEstimationProblem
  Deprecated. Build an empty instance without parameters nor measurements.
SimpleRealPointChecker - Class in org.apache.commons.math.optimization
  Simple implementation of the `RealConvergenceChecker` interface using only point coordinates.
SimpleRealPointChecker() - Constructor for class org.apache.commons.math.optimization.SimpleRealPointChecker
  Build an instance with default threshold.
SimpleRealPointChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleRealPointChecker
  Build an instance with a specified threshold.
SimpleRegression - Class in org.apache.commons.math.stat.regression
  Estimates an ordinary least squares regression model with one independent variable.
SimpleRegression() - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
  Create an empty SimpleRegression instance
SimpleRegression(TDistribution) - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
  Create an empty SimpleRegression using the given distribution object to compute inference statistics.
SimpleScalarValueChecker - Class in org.apache.commons.math.optimization
  Simple implementation of the `RealConvergenceChecker` interface using only objective function values.
SimpleScalarValueChecker() - Constructor for class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Build an instance with default threshold.
SimpleScalarValueChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleScalarValueChecker
  Build an instance with a specified threshold.
SimpleVectorialPointChecker - Class in org.apache.commons.math.optimization
  Simple implementation of the `VectorialConvergenceChecker` interface using only point coordinates.
SimpleVectorialPointChecker() - Constructor for class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Build an instance with default threshold.
SimpleVectorialPointChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleVectorialPointChecker
  Build an instance with a specified threshold.
SimpleVectorialValueChecker - Class in org.apache.commons.math.optimization
  Simple implementation of the `VectorialConvergenceChecker` interface using only objective function values.
SimpleVectorialValueChecker() - Constructor for class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Build an instance with default threshold.
SimpleVectorialValueChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleVectorialValueChecker
  Build an instance with a specified threshold.
simplex - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Simplex.
SimplexSolver - Class in org.apache.commons.math.optimization.linear
  Solves a linear problem using the Two-Phase Simplex Method.
SimplexSolver() - Constructor for class org.apache.commons.math.optimization.linear.SimplexSolver
  Build a simplex solver with default settings.
SimplexSolver(double) - Constructor for class org.apache.commons.math.optimization.linear.SimplexSolver
  Build a simplex solver with a specified accepted amount of error
SimplexTableau - Class in org.apache.commons.math.optimization.linear
  A tableau for use in the Simplex method.
SimplexTableau(LinearObjectiveFunction, Collection<LinearConstraint>, GoalType, boolean, double) - Constructor for class org.apache.commons.math.optimization.linear.SimplexTableau
  Build a tableau for a linear problem.
SimpsonIntegrator - Class in org.apache.commons.math.analysis.integration
  Implements the Simpson's Rule for integration of real univariate functions.
SimpsonIntegrator(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.integration.SimpsonIntegrator
  Deprecated. as of 2.0 the integrand function is passed as an argument to the `SimpsonIntegrator.integrate(UnivariateRealFunction, double, double)`method.
SimpsonIntegrator() - Constructor for class org.apache.commons.math.analysis.integration.SimpsonIntegrator
  Construct an integrator.
SIN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.sin` method wrapped as a `ComposableFunction`.
sin() - Method in class org.apache.commons.math.complex.Complex
  Compute the sine of this complex number.
singular - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
  Singularity indicator.
singular - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Singularity indicator.
singular - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Singularity indicator.
singular - Variable in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Singularity indicator.
SingularMatrixException - Exception in org.apache.commons.math.linear
  Thrown when a matrix is singular.
SingularMatrixException() - Constructor for exception org.apache.commons.math.linear.SingularMatrixException
  Construct an exception with a default message.
SingularValueDecomposition - Interface in org.apache.commons.math.linear
  An interface to classes that implement an algorithm to calculate the Singular Value Decomposition of a real matrix.
SingularValueDecompositionImpl - Class in org.apache.commons.math.linear
  Calculates the compact Singular Value Decomposition of a matrix.
SingularValueDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Calculates the compact Singular Value Decomposition of the given matrix.
SingularValueDecompositionImpl.Solver - Class in org.apache.commons.math.linear
  Specialized solver.
SingularValueDecompositionImpl.Solver(double[], RealMatrix, RealMatrix, boolean) - Constructor for class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Build a solver from decomposed matrix.
singularValues - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Singular values.
SINH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.sinh` method wrapped as a `ComposableFunction`.
sinh() - Method in class org.apache.commons.math.complex.Complex
  Compute the hyperbolic sine of this complex number.
sinh(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the hyperbolic sine of x.
size - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Current size of the map.
size() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Get the number of elements stored in the map.
size - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Current size of the map.
size() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Get the number of elements stored in the map.
Skewness - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the skewness of the available values.
Skewness() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
  Constructs a Skewness
Skewness(ThirdMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
  Constructs a Skewness with an external moment
Skewness(Skewness) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
  Copy constructor, creates a new `Skewness` identical to the `original`
skewnessImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Skewness statistic implementation - can be reset by setter.
smooth(double[], double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Compute a weighted loess fit on the data at the original abscissae.
smooth(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Compute a loess fit on the data at the original abscissae.
SmoothingBicubicSplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
  Generates a bicubic interpolation function.
SmoothingBicubicSplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
  Deprecated.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
  Deprecated.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
  Solve for a zero in the given interval, start at startValue.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
  Solve for a zero root in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
  Deprecated.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
  Deprecated.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
  Find a zero in the given interval with an initial guess.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
  Find a zero in the given interval.
solve(UnivariateRealFunction, double, double, double, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
  Find a zero starting search according to the three provided points.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Deprecated.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Deprecated.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Find a real root in the given interval with initial value.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Find a real root in the given interval.
solve(Complex[], Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Find a complex root for the polynomial with the given coefficients, starting from the given initial value.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
  Deprecated.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
  Deprecated.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
  Find a real root in the given interval with initial value.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
  Find a real root in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
  Deprecated.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
  Deprecated.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
  Find a zero near the midpoint of `min` and `max`.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
  Find a zero near the value `startValue`.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
  Deprecated.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
  Deprecated.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
  Find a root in the given interval with initial value.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
  Find a root in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
  Deprecated.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
  Deprecated.
solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
  Find a zero in the given interval.
solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
  Find a zero in the given interval.
solve(double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Deprecated. replaced by `UnivariateRealSolver.solve(UnivariateRealFunction, double, double)` since 2.0
solve(UnivariateRealFunction, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Solve for a zero root in the given interval.
solve(double, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Deprecated. replaced by `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` since 2.0
solve(UnivariateRealFunction, double, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
  Solve for a zero in the given interval, start at startValue.
solve(UnivariateRealFunction, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  Convenience method to find a zero of a univariate real function.
solve(UnivariateRealFunction, double, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  Convenience method to find a zero of a univariate real function.
solve(double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Deprecated.
solve(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the solution vector for a linear system with coefficient matrix = this and constant vector = `b`.
solve(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(double[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(double[]) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(RealVector) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(ArrayRealVector) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Solve the linear equation A × X = B.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(double[]) - Method in interface org.apache.commons.math.linear.DecompositionSolver
  Solve the linear equation A × X = B for matrices A.
solve(RealVector) - Method in interface org.apache.commons.math.linear.DecompositionSolver
  Solve the linear equation A × X = B for matrices A.
solve(RealMatrix) - Method in interface org.apache.commons.math.linear.DecompositionSolver
  Solve the linear equation A × X = B for matrices A.
solve(double[]) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Solve the linear equation A × X = B for symmetric matrices A.
solve(RealVector) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Solve the linear equation A × X = B for symmetric matrices A.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
  Solve the linear equation A × X = B for symmetric matrices A.
solve(T[]) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
  Solve the linear equation A × X = B for matrices A.
solve(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
  Solve the linear equation A × X = B for matrices A.
solve(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
  Solve the linear equation A × X = B for matrices A.
solve(T[]) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(FieldVector<T>) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Solve the linear equation A × X = B.
solve(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(double[]) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(RealVector) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(ArrayRealVector) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Solve the linear equation A × X = B.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(double[]) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(RealVector) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(ArrayRealVector) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Solve the linear equation A × X = B.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
  Solve the linear equation A × X = B for matrices A.
solve(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Deprecated. as of release 2.0, replaced by `DecompositionSolver.solve(double[])`
solve(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Deprecated. as of release 2.0, replaced by `DecompositionSolver.solve(RealMatrix)`
solve(double[]) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Solve the linear equation A × X = B in least square sense.
solve(RealVector) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Solve the linear equation A × X = B in least square sense.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Solve the linear equation A × X = B in least square sense.
solve2(double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
  Deprecated. replaced by `MullerSolver.solve2(UnivariateRealFunction, double, double)` since 2.0
solve2(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
  Find a real root in the given interval.
solveAll(double[], double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
solveAll(Complex[], Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
  Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
solvedCols - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
  Deprecated. Number of solved variables.
solvedCols - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
  Number of solved point.
solvePhase1(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Solves Phase 1 of the Simplex method.
solver - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  solver to use in the line search (may be null).
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Solver absolute accuracy for inverse cum computation
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.BetaDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.FDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.GammaDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.TDistributionImpl
  Inverse cumulative probability accuracy
solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Inverse cumulative probability accuracy
sortedRepresentation - Variable in class org.apache.commons.math.genetics.RandomKey
  Cache of sorted representation (unmodifiable).
sortObservations() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
  Sort the observations with respect to the abscissa.
SparseFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  Sparse matrix implementation based on an open addressed map.
SparseFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
  Creates a matrix with no data.
SparseFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
  Create a new SparseFieldMatrix<T> with the supplied row and column dimensions.
SparseFieldMatrix(SparseFieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
  Copy constructor.
SparseFieldMatrix(FieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
  Generic copy constructor.
SparseFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
  This class implements the `FieldVector` interface with a `OpenIntToFieldHashMap` backing store.
SparseFieldVector(Field<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
  Build a 0-length vector.
SparseFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
  Construct a (dimension)-length vector of zeros.
SparseFieldVector(SparseFieldVector<T>, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
  Build a resized vector, for use with append.
SparseFieldVector(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
  Build a vector with known the sparseness (for advanced use only).
SparseFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
  Create from a Field array.
SparseFieldVector(SparseFieldVector<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
  Copy constructor.
sparseIterator() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Specialized implementations may choose to not iterate over all dimensions, either because those values are unset, or are equal to defaultValue(), or are small enough to be ignored for the purposes of iteration.
sparseIterator() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Specialized implementations may choose to not iterate over all dimensions, either because those values are unset, or are equal to defaultValue(), or are small enough to be ignored for the purposes of iteration.
sparseIterator() - Method in interface org.apache.commons.math.linear.RealVector
  Specialized implementations may choose to not iterate over all dimensions, either because those values are unset, or are equal to defaultValue(), or are small enough to be ignored for the purposes of iteration.
SparseRealMatrix - Interface in org.apache.commons.math.linear
  Marker interface for `RealMatrix` implementations that require sparse backing storage
SparseRealVector - Interface in org.apache.commons.math.linear
  Marker interface for RealVectors that require sparse backing storage
SpearmansCorrelation - Class in org.apache.commons.math.stat.correlation
  Spearman's rank correlation.
SpearmansCorrelation(RealMatrix, RankingAlgorithm) - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.
SpearmansCorrelation(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Create a SpearmansCorrelation from the given data matrix.
SpearmansCorrelation() - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
  Create a SpearmansCorrelation without data.
SplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
  Computes a natural (also known as "free", "unclamped") cubic spline interpolation for the data set.
SplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SplineInterpolator
splines - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
  Set of cubic splines pacthing the whole data grid
SQRT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.sqrt` method wrapped as a `ComposableFunction`.
sqrt() - Method in class org.apache.commons.math.complex.Complex
  Compute the square root of this complex number.
sqrt1z() - Method in class org.apache.commons.math.complex.Complex
  Compute the square root of 1 - `this`2 for this complex number.
SQRT2PI - Static variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  &sqrt;(2 π)
SQRT3 - Static variable in class org.apache.commons.math.random.UniformRandomGenerator
  Square root of three.
stabilityReduction - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  stepsize reduction factor in case of stability check failure.
stage(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Compute the n-th stage integral.
stage(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Compute the n-th stage integral of trapezoid rule.
standardDeviation - Variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  The standard deviation of this distribution.
standardDeviation - Variable in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
  Standard deviation vector.
StandardDeviation - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the sample standard deviation.
StandardDeviation() - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Constructs a StandardDeviation.
StandardDeviation(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Constructs a StandardDeviation from an external second moment.
StandardDeviation(StandardDeviation) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Copy constructor, creates a new `StandardDeviation` identical to the `original`
StandardDeviation(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Contructs a StandardDeviation with the specified value for the `isBiasCorrected` property.
StandardDeviation(boolean, SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Contructs a StandardDeviation with the specified value for the `isBiasCorrected` property and the supplied external moment.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrixChangingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrixPreservingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrixChangingVisitor
  Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrixPreservingVisitor
  Start visiting a matrix.
start(double, double[], double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
  Start the integration.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Start visiting a matrix.
start() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the starting index of the internal array.
startConfiguration - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
  Start simplex configuration.
starter - Variable in class org.apache.commons.math.ode.MultistepIntegrator
  Starter integrator.
startIndex - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The position of the first addressable element in the internal storage array.
starts - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Number of starts to go.
starts - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Number of starts to go.
starts - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Number of starts to go.
starts - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Number of starts to go.
states - Variable in class org.apache.commons.math.ode.events.CombinedEventsManager
  Events states.
states - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  States table.
states - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  States table.
stateVariation - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
  State variation.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Internal weights Butcher array.
STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Internal weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Propagation weights Butcher array.
STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Propagation weights Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Time steps Butcher array.
STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Time steps Butcher array.
STATIC_E - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Error weights Butcher array.
StatisticalMultivariateSummary - Interface in org.apache.commons.math.stat.descriptive
  Reporting interface for basic multivariate statistics.
StatisticalSummary - Interface in org.apache.commons.math.stat.descriptive
  Reporting interface for basic univariate statistics.
StatisticalSummaryValues - Class in org.apache.commons.math.stat.descriptive
  Value object representing the results of a univariate statistical summary.
StatisticalSummaryValues(double, double, long, double, double, double) - Constructor for class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Constructor
statistics - Variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  The SummaryStatistics in which aggregate statistics are accumulated.
statisticsPrototype - Variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
  A SummaryStatistics serving as a prototype for creating SummaryStatistics contributing to this aggregate
StatUtils - Class in org.apache.commons.math.stat
  StatUtils provides static methods for computing statistics based on data stored in double[] arrays.
StatUtils() - Constructor for class org.apache.commons.math.stat.StatUtils
  Private Constructor
steadyStateThreshold - Variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
  Deprecated. Threshold for cost steady state detection.
step - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Integration step.
stepAccepted(double, double[]) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Inform the event handlers that the step has been accepted by the integrator.
stepAccepted(double, double[]) - Method in class org.apache.commons.math.ode.events.EventState
  Acknowledge the fact the step has been accepted by the integrator.
stepControl1 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  first stepsize control factor.
stepControl2 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  second stepsize control factor.
stepControl3 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  third stepsize control factor.
stepControl4 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  fourth stepsize control factor.
StepHandler - Interface in org.apache.commons.math.ode.sampling
  This interface represents a handler that should be called after each successful step.
stepHandlers - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Step handler.
StepHandlerWithJacobians - Interface in org.apache.commons.math.ode.jacobians
  This interface represents a handler that should be called after each successful step.
StepInterpolator - Interface in org.apache.commons.math.ode.sampling
  This interface represents an interpolator over the last step during an ODE integration.
StepInterpolatorWithJacobians - Interface in org.apache.commons.math.ode.jacobians
  This interface represents an interpolator over the last step during an ODE integration.
StepNormalizer - Class in org.apache.commons.math.ode.sampling
  This class wraps an object implementing `FixedStepHandler` into a `StepHandler`.
StepNormalizer(double, FixedStepHandler) - Constructor for class org.apache.commons.math.ode.sampling.StepNormalizer
  Simple constructor.
steps - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
  Steps table.
stepSize - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Current stepsize.
stepStart - Variable in class org.apache.commons.math.ode.AbstractIntegrator
  Current step start time.
stop() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
  Check if the integration should be stopped at the end of the current step.
STOP - Static variable in interface org.apache.commons.math.ode.events.EventHandler
  Stop indicator.
stop() - Method in class org.apache.commons.math.ode.events.EventState
  Check if the integration should be stopped at the end of the current step.
STOP - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
  Stop indicator.
StoppingCondition - Interface in org.apache.commons.math.genetics
  Algorithm used to determine when to stop evolution.
store(double, Map.Entry<RealVector, Double>) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
  Store the illumination and index of the brightest sample.
StorelessUnivariateStatistic - Interface in org.apache.commons.math.stat.descriptive
  Extends the definition of `UnivariateStatistic` with `StorelessUnivariateStatistic.increment(double)` and `StorelessUnivariateStatistic.incrementAll(double[])` methods for adding values and updating internal state.
storeTime(double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Store the current step time.
storeTime(double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Store the current step time.
storeTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Store the current step time.
stringValue - Variable in enum org.apache.commons.math.optimization.linear.Relationship
  Display string for the relationship.
subAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Subtract two integers, checking for overflow.
subAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
  Subtract two long integers, checking for overflow.
substituteMostRecentElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Substitutes `value` for the most recently added value.
SUBTRACT - Static variable in class org.apache.commons.math.analysis.BinaryFunction
  The - operator method wrapped as a `BinaryFunction`.
subtract(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Return a function subtracting another function from the instance.
subtract(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Subtract a polynomial from the instance.
subtract(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the difference between this complex number and the given complex number.
subtract(T) - Method in interface org.apache.commons.math.FieldElement
  Compute this - a.
subtract(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
  Subtracts the value of an `BigInteger` from the value of this one, returning the result in reduced form.
subtract(int) - Method in class org.apache.commons.math.fraction.BigFraction
  Subtracts the value of an `integer` from the value of this one, returning the result in reduced form.
subtract(long) - Method in class org.apache.commons.math.fraction.BigFraction
  Subtracts the value of an `integer` from the value of this one, returning the result in reduced form.
subtract(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
  Subtracts the value of another fraction from the value of this one, returning the result in reduced form.
subtract(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
  Subtracts the value of another fraction from the value of this one, returning the result in reduced form.
subtract(int) - Method in class org.apache.commons.math.fraction.Fraction
  Subtract an integer from the fraction.
subtract(Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
  Subtract a vector from the instance.
subtract(double, Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
  Subtract a scaled vector from the instance.
subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Compute this minus m.
subtract(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Compute this minus m.
subtract(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute this minus v.
subtract(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
  Compute this minus v.
subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Compute this minus m.
subtract(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Compute this minus `m`.
subtract(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Compute this minus m.
subtract(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Compute this minus `m`.
subtract(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute this minus v.
subtract(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute this minus v.
subtract(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Compute this minus v.
subtract(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute this minus v.
subtract(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute this minus v.
subtract(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Compute this minus v.
subtract(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Compute this minus m.
subtract(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Compute this minus `m`.
subtract(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Compute this minus `m`.
subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Compute this minus m.
subtract(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Compute this minus `m`.
subtract(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Compute this minus m.
subtract(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Compute this minus `m`.
subtract(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Compute this minus m.
subtract(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute this minus v.
subtract(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
  Compute this minus v.
subtract(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Compute this minus m.
subtract(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
  Compute this minus `m`.
subtract(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to subtract OpenMapRealVectors.
subtract(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute this minus v.
subtract(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute this minus v.
subtract(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Compute this minus m.
subtract(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Compute this minus m.
subtract(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Compute this minus `m`.
subtract(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
  Compute this minus v.
subtract(double[]) - Method in interface org.apache.commons.math.linear.RealVector
  Compute this minus v.
subtract(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Optimized method to subtract SparseRealVectors.
subtract(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute this minus v.
subtract(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
  Compute this minus v.
subtract(BigReal) - Method in class org.apache.commons.math.util.BigReal
  Compute this - a.
subtractRow(int, int, double) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Subtracts a multiple of one row from another.
suffix - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  Suffix.
suffix - Variable in class org.apache.commons.math.linear.RealVectorFormat
  Suffix.
sum - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  The sum of the sample values
Sum - Class in org.apache.commons.math.stat.descriptive.summary
  Returns the sum of the available values.
Sum() - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
  Create a Sum instance
Sum(Sum) - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
  Copy constructor, creates a new `Sum` identical to the `original`
sum - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  sum of values that have been added
SUM - Static variable in class org.apache.commons.math.stat.StatUtils
  sum
sum(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the values in the input array, or `Double.NaN` if the array is empty.
sum(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
SUM_OF_LOGS - Static variable in class org.apache.commons.math.stat.StatUtils
  sumLog
SUM_OF_SQUARES - Static variable in class org.apache.commons.math.stat.StatUtils
  sumSq
sumDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]).
sumImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sum statistic implementation - can be reset by setter.
sumImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sum statistic implementation - can be reset by setter.
sumImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sum statistic implementation - can be reset by setter.
sumLog - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  sumLog of values that have been added
sumLog(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the natural logs of the entries in the input array, or `Double.NaN` if the array is empty.
sumLog(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the natural logs of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
sumLogImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sum of log statistic implementation - can be reset by setter.
sumLogImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sum of log statistic implementation - can be reset by setter.
SummaryStatistics - Class in org.apache.commons.math.stat.descriptive
  Computes summary statistics for a stream of data values added using the `addValue` method.
SummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Construct a SummaryStatistics instance
SummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
  A copy constructor.
sumOfLogs - Variable in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Wrapped SumOfLogs instance
SumOfLogs - Class in org.apache.commons.math.stat.descriptive.summary
  Returns the sum of the natural logs for this collection of values.
SumOfLogs() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Create a SumOfLogs instance
SumOfLogs(SumOfLogs) - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Copy constructor, creates a new `SumOfLogs` identical to the `original`
SumOfSquares - Class in org.apache.commons.math.stat.descriptive.summary
  Returns the sum of the squares of the available values.
SumOfSquares() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Create a SumOfSquares instance
SumOfSquares(SumOfSquares) - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Copy constructor, creates a new `SumOfSquares` identical to the `original`
sums - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Sums for each component.
sumsq - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  sum of the square of each value that has been added
sumSq(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the squares of the entries in the input array, or `Double.NaN` if the array is empty.
sumSq(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the squares of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
sumsqImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Sum of squares statistic implementation - can be reset by setter.
sumSqImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Sum of squares statistic implementation - can be reset by setter.
sumsqImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Sum of squares statistic implementation - can be reset by setter.
sumX - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  sum of x values
sumXX - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  total variation in x (sum of squared deviations from xbar)
sumXY - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  sum of products
sumY - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  sum of y values
sumYY - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  total variation in y (sum of squared deviations from ybar)
SynchronizedDescriptiveStatistics - Class in org.apache.commons.math.stat.descriptive
  Implementation of `DescriptiveStatistics` that is safe to use in a multithreaded environment.
SynchronizedDescriptiveStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Construct an instance with infinite window
SynchronizedDescriptiveStatistics(int) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Construct an instance with finite window
SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  A copy constructor.
SynchronizedMultivariateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
  Implementation of `MultivariateSummaryStatistics` that is safe to use in a multithreaded environment.
SynchronizedMultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Construct a SynchronizedMultivariateSummaryStatistics instance
SynchronizedSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
  Implementation of `SummaryStatistics` that is safe to use in a multithreaded environment.
SynchronizedSummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Construct a SynchronizedSummaryStatistics instance
SynchronizedSummaryStatistics(SynchronizedSummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  A copy constructor.

## T

t(double, double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
t(double, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
t(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
t(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
t(double, double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a t statistic given observed values and a comparison constant.
t(double, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
t(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
t(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic , comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
t(double, double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a t statistic given observed values and a comparison constant.
t(double, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
t(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
t(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic , comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
t(double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes t test statistic for 1-sample t-test.
t(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes t test statistic for 2-sample t-test.
t0 - Variable in class org.apache.commons.math.ode.events.EventState
  Time at the beginning of the step.
tableau - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
  Simple tableau.
TAN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.tan` method wrapped as a `ComposableFunction`.
tan() - Method in class org.apache.commons.math.complex.Complex
  Compute the tangent of this complex number.
TANH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.tanh` method wrapped as a `ComposableFunction`.
tanh() - Method in class org.apache.commons.math.complex.Complex
  Compute the hyperbolic tangent of this complex number.
targetValues - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Target value for the objective functions at optimum.
TDistribution - Interface in org.apache.commons.math.distribution
  Student's t-Distribution.
TDistributionImpl - Class in org.apache.commons.math.distribution
  Default implementation of `TDistribution`.
TDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.TDistributionImpl
  Create a t distribution using the given degrees of freedom and the specified inverse cumulative probability absolute accuracy.
TDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.TDistributionImpl
  Create a t distribution using the given degrees of freedom.
test(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  This method is used by `evaluate(double[], int, int)` methods to verify that the input parameters designate a subarray of positive length.
test(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  This method is used by `evaluate(double[], double[], int, int)` methods to verify that the begin and length parameters designate a subarray of positive length and the weights are all non-negative, non-NaN, finite, and not all zero.
TestUtils - Class in org.apache.commons.math.stat.inference
  A collection of static methods to create inference test instances or to perform inference tests.
TestUtils() - Constructor for class org.apache.commons.math.stat.inference.TestUtils
  Prevent instantiation.
ThirdMoment - Class in org.apache.commons.math.stat.descriptive.moment
  Computes a statistic related to the Third Central Moment.
ThirdMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Create a FourthMoment instance
ThirdMoment(ThirdMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Copy constructor, creates a new `ThirdMoment` identical to the `original`
THREE_FIFTHS - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "3/5".
THREE_FIFTHS - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "3/5".
THREE_QUARTERS - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "3/4".
THREE_QUARTERS - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "3/4".
ThreeEighthesIntegrator - Class in org.apache.commons.math.ode.nonstiff
  This class implements the 3/8 fourth order Runge-Kutta integrator for Ordinary Differential Equations.
ThreeEighthesIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Simple constructor.
ThreeEighthesStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
  This class implements a step interpolator for the 3/8 fourth order Runge-Kutta integrator.
ThreeEighthesStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
  Simple constructor.
ThreeEighthesStepInterpolator(ThreeEighthesStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
  Copy constructor.
tiesStrategy - Variable in class org.apache.commons.math.stat.ranking.NaturalRanking
  Ties strategy - defaults to ties averaged
TiesStrategy - Enum in org.apache.commons.math.stat.ranking
  Strategies for handling tied values in rank transformations.
TiesStrategy() - Constructor for enum org.apache.commons.math.stat.ranking.TiesStrategy
tmp - Variable in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
  Temporary entry (reused on each call to `AbstractRealVector.SparseEntryIterator.next()`.
tmpDot - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
  Temporary array for state derivatives used to compute jacobians.
toArray() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Convert the vector to a double array.
toArray() - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Convert the vector to a T array.
toArray() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Convert the vector to a double array.
toArray() - Method in interface org.apache.commons.math.linear.FieldVector
  Convert the vector to a T array.
toArray() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Convert the vector to a double array.
toArray() - Method in interface org.apache.commons.math.linear.RealVector
  Convert the vector to a double array.
toArray() - Method in class org.apache.commons.math.linear.SparseFieldVector
  Convert the vector to a T array.
toBlocksLayout(T[][]) - Static method in class org.apache.commons.math.linear.BlockFieldMatrix
  Convert a data array from raw layout to blocks layout.
toBlocksLayout(double[][]) - Static method in class org.apache.commons.math.linear.BlockRealMatrix
  Convert a data array from raw layout to blocks layout.
TOO_SMALL - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Bound to determine effective singularity in LU decomposition
toString() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Returns a string representation of the polynomial.
toString() - Method in class org.apache.commons.math.fraction.BigFraction
  Returns the `String` representing this fraction, ie "num / dem" or just "num" if the denominator is one.
toString() - Method in class org.apache.commons.math.fraction.Fraction
  Returns the `String` representing this fraction, ie "num / dem" or just "num" if the denominator is one.
toString() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
toString() - Method in class org.apache.commons.math.genetics.ChromosomePair
toString() - Method in class org.apache.commons.math.genetics.ListPopulation
toString() - Method in class org.apache.commons.math.genetics.RandomKey
toString() - Method in class org.apache.commons.math.geometry.RotationOrder
  Get a string representation of the instance.
toString() - Method in class org.apache.commons.math.geometry.Vector3D
  Get a string representation of this vector.
toString() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Get a string representation for this matrix.
toString() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Get a string representation for this matrix.
toString() - Method in class org.apache.commons.math.linear.ArrayRealVector
toString() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Get a string representation for this matrix.
toString() - Method in enum org.apache.commons.math.optimization.linear.Relationship
toString() - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
toString() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Generates a text report displaying univariate statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
  Generates a text report displaying univariate statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
  Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
  Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.Frequency
  Return a string representation of this frequency distribution.
totalEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Number of evaluations already performed for all starts.
totalEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Number of evaluations already performed for all starts.
totalEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Number of evaluations already performed for all starts.
totalEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Number of evaluations already performed for all starts.
totalGradientEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Number of gradient evaluations already performed for all starts.
totalIterations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
  Number of iterations already performed for all starts.
totalIterations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Number of iterations already performed for all starts.
totalIterations - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
  Number of iterations already performed for all starts.
totalIterations - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
  Number of iterations already performed for all starts.
totalJacobianEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
  Number of jacobian evaluations already performed for all starts.
tournament(ListPopulation) - Method in class org.apache.commons.math.genetics.TournamentSelection
  Helper for `TournamentSelection.select(Population)`.
TournamentSelection - Class in org.apache.commons.math.genetics
  Tournament selection scheme.
TournamentSelection(int) - Constructor for class org.apache.commons.math.genetics.TournamentSelection
  Creates a new TournamentSelection instance.
transform() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
  Transform original matrix to tridiagonal form.
transform(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Transform the given real data set.
transform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Transform the given real function, sampled on the given interval.
transform(double[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Transform the given real data set.
transform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Transform the given real function, sampled on the given interval.
transform(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Transform the given complex data set.
transform(double[]) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  Transform the given real data set.
transform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  Transform the given real function, sampled on the given interval.
transform(int[]) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
  Transform the given real data set.
transform(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Transform the given real data set.
transform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Transform the given real function, sampled on the given interval.
transform(double[]) - Method in interface org.apache.commons.math.transform.RealTransformer
  Transform the given real data set.
transform(UnivariateRealFunction, double, double, int) - Method in interface org.apache.commons.math.transform.RealTransformer
  Transform the given real function, sampled on the given interval.
transform(Object) - Method in class org.apache.commons.math.util.DefaultTransformer
transform(Object) - Method in interface org.apache.commons.math.util.NumberTransformer
  Implementing this interface provides a facility to transform from Object to Double.
transform(Object) - Method in class org.apache.commons.math.util.TransformerMap
  Attempts to transform the Object against the map of NumberTransformers.
transform2(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Transform the given real data set.
transform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastCosineTransformer
  Transform the given real function, sampled on the given interval.
transform2(double[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Transform the given real data set.
transform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Transform the given real function, sampled on the given interval.
transform2(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
  Transform the given complex data set.
transform2(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Transform the given real data set.
transform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastSineTransformer
  Transform the given real function, sampled on the given interval.
transformer - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Transformer to tridiagonal (may be null if matrix is already tridiagonal).
transformer - Variable in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Transformer.
TransformerMap - Class in org.apache.commons.math.util
  This TansformerMap automates the transformation of mixed object types.
TransformerMap() - Constructor for class org.apache.commons.math.util.TransformerMap
  Build a map containing only the default transformer.
transformers() - Method in class org.apache.commons.math.util.TransformerMap
  Returns the Set of NumberTransformers used as values in the map.
transformToLowerBiDiagonal() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Transform original matrix to lower bi-diagonal form.
transformToTridiagonal(RealMatrix) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Transform matrix to tridiagonal.
transformToUpperBiDiagonal() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
  Transform original matrix to upper bi-diagonal form.
translate(String, Locale) - Static method in exception org.apache.commons.math.MathException
  Translate a string to a given locale.
translate(String, Locale) - Static method in exception org.apache.commons.math.MathRuntimeException
  Translate a string to a given locale.
transpose() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Returns the transpose of this matrix.
transpose() - Method in interface org.apache.commons.math.linear.BigMatrix
  Deprecated. Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Returns the transpose matrix.
transpose() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Returns the transpose of this matrix.
transpose() - Method in interface org.apache.commons.math.linear.FieldMatrix
  Returns the transpose of this matrix.
transpose() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the transpose of this matrix.
TrapezoidIntegrator - Class in org.apache.commons.math.analysis.integration
  Implements the Trapezoidal Rule for integration of real univariate functions.
TrapezoidIntegrator(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Deprecated. as of 2.0 the integrand function is passed as an argument to the `TrapezoidIntegrator.integrate(UnivariateRealFunction, double, double)`method.
TrapezoidIntegrator() - Constructor for class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Construct an integrator.
tricube(double) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Compute the tricube weight function
TriDiagonalTransformer - Class in org.apache.commons.math.linear
  Class transforming a symmetrical matrix to tridiagonal shape.
TriDiagonalTransformer(RealMatrix) - Constructor for class org.apache.commons.math.linear.TriDiagonalTransformer
  Build the transformation to tridiagonal shape of a symmetrical matrix.
trigamma(double) - Static method in class org.apache.commons.math.special.Gamma
  Computes the trigamma function of x.
trimmedPrefix - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  Trimmed prefix.
trimmedPrefix - Variable in class org.apache.commons.math.linear.RealVectorFormat
  Trimmed prefix.
trimmedSeparator - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  Trimmed separator.
trimmedSeparator - Variable in class org.apache.commons.math.linear.RealVectorFormat
  Trimmed separator.
trimmedSuffix - Variable in class org.apache.commons.math.geometry.Vector3DFormat
  Trimmed suffix.
trimmedSuffix - Variable in class org.apache.commons.math.linear.RealVectorFormat
  Trimmed suffix.
tryStep(double, double[], double, int, double[], double[][], double[], double[], double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Perform integration over one step using substeps of a modified midpoint method.
tTest - Static variable in class org.apache.commons.math.stat.inference.TestUtils
  Singleton TTest instance using default implementation.
tTest(double, double[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(double, double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(double, StatisticalSummary, double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(double, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(double[], double[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(StatisticalSummary, StatisticalSummary, double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
tTest(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
TTest - Interface in org.apache.commons.math.stat.inference
  An interface for Student's t-tests.
tTest(double, double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant `mu`.
tTest(double, double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which `sample` is drawn equals `mu`.
tTest(double, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
tTest(double, StatisticalSummary, double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
tTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
tTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
tTest(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
tTest(StatisticalSummary, StatisticalSummary, double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.
tTest(double, double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant `mu`.
tTest(double, double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which `sample` is drawn equals `mu`.
tTest(double, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
tTest(double, StatisticalSummary, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
tTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
tTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
tTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
tTest(StatisticalSummary, StatisticalSummary, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.
tTest(double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes p-value for 2-sided, 1-sample t-test.
tTest(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes p-value for 2-sided, 2-sample t-test.
TTestImpl - Class in org.apache.commons.math.stat.inference
  Implements t-test statistics defined in the `TTest` interface.
TTestImpl() - Constructor for class org.apache.commons.math.stat.inference.TTestImpl
  Default constructor.
TTestImpl(TDistribution) - Constructor for class org.apache.commons.math.stat.inference.TTestImpl
  Create a test instance using the given distribution for computing inference statistics.
TWO - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "2 / 1".
TWO - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "2 / 1".
TWO_FIFTHS - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "2/5".
TWO_FIFTHS - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "2/5".
TWO_MINUS_SQRT_2 - Static variable in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  First Gill coefficient.
TWO_PI - Static variable in class org.apache.commons.math.util.MathUtils
  2 π.
TWO_PLUS_SQRT_2 - Static variable in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Second Gill coefficient.
TWO_QUARTERS - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "2/4".
TWO_QUARTERS - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "2/4".
TWO_THIRDS - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "2/3".
TWO_THIRDS - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "2/3".

## U

ULP - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The `Math.ulp` method wrapped as a `ComposableFunction`.
UnboundedSolutionException - Exception in org.apache.commons.math.optimization.linear
  This class represents exceptions thrown by optimizers when a solution escapes to infinity.
UnboundedSolutionException() - Constructor for exception org.apache.commons.math.optimization.linear.UnboundedSolutionException
  Simple constructor using a default message.
UncorrelatedRandomVectorGenerator - Class in org.apache.commons.math.random
  A `RandomVectorGenerator` that generates vectors with uncorrelated components.
UncorrelatedRandomVectorGenerator(double[], double[], NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
  Simple constructor.
UncorrelatedRandomVectorGenerator(int, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
  Simple constructor.
UNIFORM_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Uniform random deviates with mean = μ.
UniformRandomGenerator - Class in org.apache.commons.math.random
  This class implements a normalized uniform random generator.
UniformRandomGenerator(RandomGenerator) - Constructor for class org.apache.commons.math.random.UniformRandomGenerator
  Create a new generator.
unitize() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Converts this vector into a unit vector.
unitize() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Converts this vector into a unit vector.
unitize() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Converts this vector into a unit vector.
unitize() - Method in interface org.apache.commons.math.linear.RealVector
  Converts this vector into a unit vector.
UnitSphereRandomVectorGenerator - Class in org.apache.commons.math.random
  Generate random vectors isotropically located on the surface of a sphere.
UnitSphereRandomVectorGenerator(int, RandomGenerator) - Constructor for class org.apache.commons.math.random.UnitSphereRandomVectorGenerator
UnitSphereRandomVectorGenerator(int) - Constructor for class org.apache.commons.math.random.UnitSphereRandomVectorGenerator
  Create an object that will use a default RNG (`MersenneTwister`), in order to generate the individual components.
unitVector() - Method in class org.apache.commons.math.linear.AbstractRealVector
  Creates a unit vector pointing in the direction of this vector.
unitVector() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Creates a unit vector pointing in the direction of this vector.
unitVector() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Creates a unit vector pointing in the direction of this vector.
unitVector() - Method in interface org.apache.commons.math.linear.RealVector
  Creates a unit vector pointing in the direction of this vector.
UnivariateMatrixFunction - Interface in org.apache.commons.math.analysis
  An interface representing a univariate matrix function.
UnivariateRealFunction - Interface in org.apache.commons.math.analysis
  An interface representing a univariate real function.
UnivariateRealIntegrator - Interface in org.apache.commons.math.analysis.integration
  Interface for univariate real integration algorithms.
UnivariateRealIntegratorImpl - Class in org.apache.commons.math.analysis.integration
  Provide a default implementation for several generic functions.
UnivariateRealIntegratorImpl(UnivariateRealFunction, int) - Constructor for class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Deprecated. as of 2.0 the integrand function is passed as an argument to the `UnivariateRealIntegrator.integrate(UnivariateRealFunction, double, double)`method.
UnivariateRealIntegratorImpl(int) - Constructor for class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Construct an integrator with given iteration count and accuracy.
UnivariateRealInterpolator - Interface in org.apache.commons.math.analysis.interpolation
  Interface representing a univariate real interpolating function.
UnivariateRealOptimizer - Interface in org.apache.commons.math.optimization
  Interface for (univariate real) optimization algorithms.
UnivariateRealSolver - Interface in org.apache.commons.math.analysis.solvers
  Interface for (univariate real) rootfinding algorithms.
UnivariateRealSolverFactory - Class in org.apache.commons.math.analysis.solvers
  Abstract factory class used to create `UnivariateRealSolver` instances.
UnivariateRealSolverFactory() - Constructor for class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
  Default constructor.
UnivariateRealSolverFactoryImpl - Class in org.apache.commons.math.analysis.solvers
  A concrete `UnivariateRealSolverFactory`.
UnivariateRealSolverFactoryImpl() - Constructor for class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
  Default constructor.
UnivariateRealSolverImpl - Class in org.apache.commons.math.analysis.solvers
  Provide a default implementation for several functions useful to generic solvers.
UnivariateRealSolverImpl(UnivariateRealFunction, int, double) - Constructor for class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Deprecated. as of 2.0 the function to solve is passed as an argument to the `UnivariateRealSolver.solve(UnivariateRealFunction, double, double)` or `UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)` method.
UnivariateRealSolverImpl(int, double) - Constructor for class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Construct a solver with given iteration count and accuracy.
UnivariateRealSolverUtils - Class in org.apache.commons.math.analysis.solvers
  Utility routines for `UnivariateRealSolver` objects.
UnivariateRealSolverUtils() - Constructor for class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
  Default constructor.
UnivariateRealSolverUtils.LazyHolder - Class in org.apache.commons.math.analysis.solvers
  Holder for the factory.
UnivariateRealSolverUtils.LazyHolder() - Constructor for class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils.LazyHolder
UnivariateStatistic - Interface in org.apache.commons.math.stat.descriptive
  Base interface implemented by all statistics.
UnivariateVectorialFunction - Interface in org.apache.commons.math.analysis
  An interface representing a univariate vectorial function.
unknownDistributionChiSquareTest - Static variable in class org.apache.commons.math.stat.inference.TestUtils
  Singleton ChiSquareTest instance using default implementation.
UnknownDistributionChiSquareTest - Interface in org.apache.commons.math.stat.inference
  An interface for Chi-Square tests for unknown distributions.
UNSUPPORTED_METHOD_MESSAGE - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Message for unsupported setQuantile.
update - Variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Update matrix for the higher order derivatives h2/2y'', h3/6 y''' ...
updateBandwidthInterval(double[], double[], int, int[]) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Given an index interval into xval that embraces a certain number of points closest to xval[i-1], update the interval so that it embraces the same number of points closest to xval[i], ignoring zero weights.
updateFormula - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
  Update formula for the beta parameter.
updateHighOrderDerivativesPhase1(Array2DRowRealMatrix) - Method in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Update the high order scaled derivatives for Adams integrators (phase 1).
updateHighOrderDerivativesPhase1(Array2DRowRealMatrix) - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Update the high order scaled derivatives for Adams integrators (phase 1).
updateHighOrderDerivativesPhase2(double[], double[], Array2DRowRealMatrix) - Method in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
  Update the high order scaled derivatives Adams integrators (phase 2).
updateHighOrderDerivativesPhase2(double[], double[], Array2DRowRealMatrix) - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
  Update the high order scaled derivatives Adams integrators (phase 2).
updateJacobian() - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Update the jacobian matrix.
updateJacobian() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Update the jacobian matrix.
updateResidualsAndCost() - Method in class org.apache.commons.math.estimation.AbstractEstimator
  Deprecated. Update the residuals array and cost function value.
updateResidualsAndCost() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Update the residuals array and cost function value.
upperBounds - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  upper bounds of subintervals in (0,1) "belonging" to the bins
upperCumulativeProbability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For this distribution, X, this method returns P(X ≥ x).
UPSIDE_VARIANCE - Static variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  The UPSIDE Direction is used to specify that the observations above the cutoff point will be used to calculate SemiVariance.
useInterpolationError - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  use interpolation error in stepsize control.
useLU - Variable in class org.apache.commons.math.optimization.general.GaussNewtonOptimizer
  Indicator for using LU decomposition.

## V

v - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Vectors for interpolation.
v1 - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  First vector for interpolation.
v2 - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Second vector for interpolation.
v3 - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Third vector for interpolation.
v4 - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Fourth vector for interpolation.
validateCovarianceData(double[][], double[][]) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Validates sample data.
validateSampleData(double[][], double[]) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Validates sample data.
value(double, double) - Method in class org.apache.commons.math.analysis.BinaryFunction
  Compute the value for the function.
value(double, double) - Method in interface org.apache.commons.math.analysis.BivariateRealFunction
  Compute the value for the function.
value(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
  Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
value(double, double) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
  Compute the value for the function.
value(double[]) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
value(double[]) - Method in interface org.apache.commons.math.analysis.MultivariateMatrixFunction
  Compute the value for the function at the given point.
value(double[]) - Method in interface org.apache.commons.math.analysis.MultivariateRealFunction
  Compute the value for the function at the given point.
value(double[]) - Method in interface org.apache.commons.math.analysis.MultivariateVectorialFunction
  Compute the value for the function at the given point.
value(double) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
  Compute the value of the function for the given argument.
value(double) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Calculate the function value at the given point.
value(double) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Calculate the function value at the given point.
value(double) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
  Compute the value for the function.
value(double) - Method in interface org.apache.commons.math.analysis.UnivariateMatrixFunction
  Compute the value for the function.
value(double) - Method in interface org.apache.commons.math.analysis.UnivariateRealFunction
  Compute the value for the function.
value(double) - Method in interface org.apache.commons.math.analysis.UnivariateVectorialFunction
  Compute the value for the function.
value(double[]) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter.TheoreticalValuesFunction
  Compute the value for the function at the given point.
value(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter.ParametricHarmonicFunction
  Compute the value of the function.
value(double) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
  Compute the value for the function.
value(double, double[]) - Method in interface org.apache.commons.math.optimization.fitting.ParametricRealFunction
  Compute the value of the function.
value(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter.ParametricPolynomial
  Compute the value of the function.
value(double) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.LineSearchFunction
  Compute the value for the function.
value(double[]) - Method in class org.apache.commons.math.optimization.LeastSquaresConverter
  Compute the value for the function at the given point.
value - Variable in class org.apache.commons.math.optimization.linear.LinearConstraint
  Value of the constraint (right hand side).
value - Variable in class org.apache.commons.math.optimization.RealPointValuePair
  Value of the objective function at the point.
value - Variable in class org.apache.commons.math.optimization.VectorialPointValuePair
  Vectorial value of the objective function at the point.
value - Variable in class org.apache.commons.math.stat.descriptive.rank.Max
  Current value of the statistic
value - Variable in class org.apache.commons.math.stat.descriptive.rank.Min
  Current value of the statistic
value - Variable in class org.apache.commons.math.stat.descriptive.summary.Product
  The current Running Product.
value - Variable in class org.apache.commons.math.stat.descriptive.summary.Sum
  The currently running sum.
value - Variable in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  The currently running value
value - Variable in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  The currently running sumSq
value - Variable in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
  Value of the pair
value() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
  Get the value of current entry.
value() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
  Get the value of current entry.
valueOf(String) - Static method in enum org.apache.commons.math.optimization.general.ConjugateGradientFormula
  Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math.optimization.GoalType
  Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math.optimization.linear.Relationship
  Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
  Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math.stat.ranking.NaNStrategy
  Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math.stat.ranking.TiesStrategy
  Returns the enum constant of this type with the specified name.
values() - Static method in enum org.apache.commons.math.optimization.general.ConjugateGradientFormula
  Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math.optimization.GoalType
  Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math.optimization.linear.Relationship
  Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
  Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math.stat.ranking.NaNStrategy
  Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math.stat.ranking.TiesStrategy
  Returns an array containing the constants of this enum type, in the order they are declared.
values - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
  Values table.
values - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
  Values table.
ValueServer - Class in org.apache.commons.math.random
  Generates values for use in simulation applications.
ValueServer() - Constructor for class org.apache.commons.math.random.ValueServer
  Creates new ValueServer
ValueServer(RandomData) - Constructor for class org.apache.commons.math.random.ValueServer
  Construct a ValueServer instance using a RandomData as its source of random data.
valuesFileURL - Variable in class org.apache.commons.math.random.ValueServer
  URI to raw data values.
valuesIterator() - Method in class org.apache.commons.math.stat.Frequency
  Returns an Iterator over the set of values that have been added.
variance - Variable in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Wrapped Variance instance
Variance - Class in org.apache.commons.math.stat.descriptive.moment
  Computes the variance of the available values.
Variance() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance with default (true) `isBiasCorrected` property.
Variance(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance based on an external second moment.
Variance(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance with the specified `isBiasCorrected` property
Variance(boolean, SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance with the specified `isBiasCorrected` property and the supplied external second moment.
Variance(Variance) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Copy constructor, creates a new `Variance` identical to the `original`
variance - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  The sample variance
variance - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  variance of values that have been added
VARIANCE - Static variable in class org.apache.commons.math.stat.StatUtils
  variance
variance(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the input array, or `Double.NaN` if the array is empty.
variance(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
variance(double[], double, int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
variance(double[], double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the input array, using the precomputed mean value.
varianceDifference(double[], double[], double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]).
varianceDirection - Variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
  Determines whether to calculate downside or upside SemiVariance.
varianceImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Variance statistic implementation - can be reset by setter.
varianceImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Variance statistic implementation - can be reset by setter.
vecAbsoluteTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Allowed absolute vectorial error.
vecRelativeTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
  Allowed relative vectorial error.
Vector3D - Class in org.apache.commons.math.geometry
  This class implements vectors in a three-dimensional space.
Vector3D(double, double, double) - Constructor for class org.apache.commons.math.geometry.Vector3D
  Simple constructor.
Vector3D(double, double) - Constructor for class org.apache.commons.math.geometry.Vector3D
  Simple constructor.
Vector3D(double, Vector3D) - Constructor for class org.apache.commons.math.geometry.Vector3D
  Multiplicative constructor Build a vector from another one and a scale factor.
Vector3D(double, Vector3D, double, Vector3D) - Constructor for class org.apache.commons.math.geometry.Vector3D
  Linear constructor Build a vector from two other ones and corresponding scale factors.
Vector3D(double, Vector3D, double, Vector3D, double, Vector3D) - Constructor for class org.apache.commons.math.geometry.Vector3D
  Linear constructor Build a vector from three other ones and corresponding scale factors.
Vector3D(double, Vector3D, double, Vector3D, double, Vector3D, double, Vector3D) - Constructor for class org.apache.commons.math.geometry.Vector3D
  Linear constructor Build a vector from four other ones and corresponding scale factors.
Vector3DFormat - Class in org.apache.commons.math.geometry
  Formats a 3D vector in components list format "{x; y; z}".
Vector3DFormat() - Constructor for class org.apache.commons.math.geometry.Vector3DFormat
  Create an instance with default settings.
Vector3DFormat(NumberFormat) - Constructor for class org.apache.commons.math.geometry.Vector3DFormat
  Create an instance with a custom number format for components.
Vector3DFormat(String, String, String) - Constructor for class org.apache.commons.math.geometry.Vector3DFormat
  Create an instance with custom prefix, suffix and separator.
Vector3DFormat(String, String, String, NumberFormat) - Constructor for class org.apache.commons.math.geometry.Vector3DFormat
  Create an instance with custom prefix, suffix, separator and format for components.
VECTOR_LENGTH_MISMATCH_MESSAGE - Static variable in class org.apache.commons.math.linear.LUDecompositionImpl
  Message for vector length mismatch.
VECTOR_LENGTHS_MISMATCH - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Message for vector lengths mismatch.
VECTOR_LENGTHS_MISMATCH - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Message for vector lengths mismatch.
VectorialConvergenceChecker - Interface in org.apache.commons.math.optimization
  This interface specifies how to check if a `optimization algorithm` has converged.
VectorialCovariance - Class in org.apache.commons.math.stat.descriptive.moment
  Returns the covariance matrix of the available vectors.
VectorialCovariance(int, boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
  Constructs a VectorialCovariance.
VectorialMean - Class in org.apache.commons.math.stat.descriptive.moment
  Returns the arithmetic mean of the available vectors.
VectorialMean(int) - Constructor for class org.apache.commons.math.stat.descriptive.moment.VectorialMean
  Constructs a VectorialMean.
VectorialPointValuePair - Class in org.apache.commons.math.optimization
  This class holds a point and the vectorial value of an objective function at this point.
VectorialPointValuePair(double[], double[]) - Constructor for class org.apache.commons.math.optimization.VectorialPointValuePair
  Build a point/objective function value pair.
VectorialPointValuePair(double[], double[], boolean) - Constructor for class org.apache.commons.math.optimization.VectorialPointValuePair
  Build a point/objective function value pair.
vectorsInitialized - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
  Initialization indicator for the interpolation vectors.
vectorsInitialized - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Initialization indicator for the interpolation vectors.
verifyBracketing(double, double, UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Verifies that the endpoints specify an interval and the function takes opposite signs at the enpoints, throws IllegalArgumentException if not
verifyDataSet(double[]) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Verifies that the data set has length of power of 2.
verifyDataSet(Object[]) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Verifies that the data set has length of power of 2.
verifyInputArray(double[], double[]) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
  Verifies that the input arrays are valid.
verifyInterpolationArray(double[], double[]) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Verifies that the interpolation arrays are valid.
verifyInterval(double, double) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Verifies that the endpoints specify an interval.
verifyInterval(double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Verifies that the endpoints specify an interval, throws IllegalArgumentException if not
verifyInterval(double, double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Verifies that the endpoints specify an interval.
verifyIterationCount() - Method in class org.apache.commons.math.analysis.integration.RombergIntegrator
  Verifies that the upper and lower limits of iterations are valid.
verifyIterationCount() - Method in class org.apache.commons.math.analysis.integration.SimpsonIntegrator
  Verifies that the upper and lower limits of iterations are valid.
verifyIterationCount() - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
  Verifies that the upper and lower limits of iterations are valid.
verifyIterationCount() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
  Verifies that the upper and lower limits of iterations are valid.
verifySequence(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
  Verifies that `lower < initial < upper` throws IllegalArgumentException if not
virtualSize - Variable in class org.apache.commons.math.linear.OpenMapRealVector
  Dimension of the vector.
virtualSize - Variable in class org.apache.commons.math.linear.SparseFieldVector
  Dimension of the vector.
visit(int, int, T) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
  Visit one matrix entry.
visit(int, int, T) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
  Visit one matrix entry.
visit(int, int, double) - Method in class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
  Visit one matrix entry.
visit(int, int, double) - Method in class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
  Visit one matrix entry.
visit(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrixChangingVisitor
  Visit one matrix entry.
visit(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrixPreservingVisitor
  Visit one matrix entry.
visit(int, int, BigFraction) - Method in class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
  Visit one matrix entry.
visit(int, int, Fraction) - Method in class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
  Visit one matrix entry.
visit(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrixChangingVisitor
  Visit one matrix entry.
visit(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrixPreservingVisitor
  Visit one matrix entry.
visit(int, int, double) - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
  Visit one matrix entry.

## W

walkInColumnOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (but don't change) some matrix entries in column order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (but don't change) some matrix entries using the fastest possible order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Deprecated. Visit (but don't change) some matrix entries in row order.
WeibullDistribution - Interface in org.apache.commons.math.distribution
  Weibull Distribution.
WeibullDistributionImpl - Class in org.apache.commons.math.distribution
  Default implementation of `WeibullDistribution`.
WeibullDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.WeibullDistributionImpl
  Creates weibull distribution with the given shape and scale and a location equal to zero.
WeibullDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.WeibullDistributionImpl
  Creates weibull distribution with the given shape, scale and inverse cumulative probability accuracy and a location equal to zero.
weight - Variable in class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Measurement weight.
weight - Variable in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Weight of the measurement in the fitting process.
WeightedEvaluation - Interface in org.apache.commons.math.stat.descriptive
  Weighted evaluation for statistics.
WeightedMeasurement - Class in org.apache.commons.math.estimation
  Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general
WeightedMeasurement(double, double) - Constructor for class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Simple constructor.
WeightedMeasurement(double, double, boolean) - Constructor for class org.apache.commons.math.estimation.WeightedMeasurement
  Deprecated. Simple constructor.
WeightedObservedPoint - Class in org.apache.commons.math.optimization.fitting
  This class is a simple container for weighted observed point in `curve fitting`.
WeightedObservedPoint(double, double, double) - Constructor for class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Simple constructor.
weights - Variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Weights for the current method.
weights - Variable in class org.apache.commons.math.optimization.LeastSquaresConverter
  Optional weights for the residuals.
WEIGHTS_2 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Weights for the 2 points method.
WEIGHTS_3 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Weights for the 3 points method.
WEIGHTS_4 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Weights for the 4 points method.
WEIGHTS_5 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
  Weights for the 5 points method.
wholeFormat - Variable in class org.apache.commons.math.fraction.ProperBigFractionFormat
  The format used for the whole number.
wholeFormat - Variable in class org.apache.commons.math.fraction.ProperFractionFormat
  The format used for the whole number.
windowSize - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  hold the window size
writeArray(ObjectOutput, double[]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Write an array.
writeArray(ObjectOutput, double[][]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Write an array.
writeBaseExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
  Save the base state of the instance.
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
  Write the instance to an output channel.
writeExternal(ObjectOutput) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
writeObject(ObjectOutputStream) - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
  Serialize the instance.
writeObject(ObjectOutputStream) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
  Serialize the instance.
writeObject(ObjectOutputStream) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Serialize the instance.
WRONG_ORDER_ENDPOINTS_MESSAGE - Static variable in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Message for endpoints in wrong order.

## X

x - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Interpolating points (abscissas).
x - Variable in class org.apache.commons.math.geometry.Vector3D
  Abscissa.
x - Variable in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Abscissa of the point.
X - Variable in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  X sample data.
xbar - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  mean of accumulated x values, used in updating formulas
xval - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
  Samples x-coordinates
XYX - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Euler angles.
XYZ - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Cardan angles.
XZX - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Euler angles.
XZY - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Cardan angles.

## Y

y - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Function values at interpolating points.
y - Variable in class org.apache.commons.math.geometry.Vector3D
  Ordinate.
y - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
  State array.
y - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Current state.
y - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  State array.
y - Variable in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
  Observed value of the function at x.
Y - Variable in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
  Y sample data.
y0Dot - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Slope at the beginning of the step.
y1 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  State at the end of the step.
y1Dot - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Slope at the end of the step.
ybar - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
  mean of accumulated y values, used in updating formulas
yDot - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
  Time derivative of the current state.
yDot - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
  Time derivative of the state array.
yDotK - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
  Slopes at the intermediate points
yDotKLast - Variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
  Last evaluations.
yMidDots - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
  Derivatives at the middle of the step.
yval - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
  Samples y-coordinates
YXY - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Euler angles.
YXZ - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Cardan angles.
YZX - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Cardan angles.
YZY - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Euler angles.

## Z

z - Variable in class org.apache.commons.math.distribution.BetaDistributionImpl
  Normalizing factor used in density computations.
z - Variable in class org.apache.commons.math.geometry.Vector3D
  Height.
z - Variable in class org.apache.commons.math.ode.FirstOrderConverter
  state vector.
ZB - Static variable in class org.apache.commons.math.util.MathUtils
  0.0 cast as a byte.
zDDot - Variable in class org.apache.commons.math.ode.FirstOrderConverter
  second time derivative of the state vector.
zDot - Variable in class org.apache.commons.math.ode.FirstOrderConverter
  first time derivative of the state vector.
ZERO - Static variable in class org.apache.commons.math.analysis.ComposableFunction
  The constant function always returning 0.
ZERO - Static variable in class org.apache.commons.math.complex.Complex
  A complex number representing "0.0 + 0.0i"
ZERO - Static variable in class org.apache.commons.math.fraction.BigFraction
  A fraction representing "0".
ZERO - Static variable in class org.apache.commons.math.fraction.Fraction
  A fraction representing "0".
ZERO - Static variable in class org.apache.commons.math.geometry.Vector3D
  Null vector (coordinates: 0, 0, 0).
ZERO - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. BigDecimal 0
zero - Variable in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
  Zero element of the field.
zero - Variable in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
  Zero element of the field.
ZERO - Static variable in class org.apache.commons.math.util.BigReal
  A big real representing 0.
ZERO_DENOMINATOR_MESSAGE - Static variable in class org.apache.commons.math.fraction.Fraction
  Message for zero denominator.
ZipfDistribution - Interface in org.apache.commons.math.distribution
  The Zipf (or zeta) Distribution.
ZipfDistributionImpl - Class in org.apache.commons.math.distribution
  Implementation for the `ZipfDistribution`.
ZipfDistributionImpl(int, double) - Constructor for class org.apache.commons.math.distribution.ZipfDistributionImpl
  Create a new Zipf distribution with the given number of elements and exponent.
ZS - Static variable in class org.apache.commons.math.util.MathUtils
  0.0 cast as a short.
ZXY - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Cardan angles.
ZXZ - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Euler angles.
ZYX - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Cardan angles.
ZYZ - Static variable in class org.apache.commons.math.geometry.RotationOrder
  Set of Euler angles.

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