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
  Members of c[] are called centers of the Newton polynomial.
a - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Internal weights Butcher array.
a - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Internal weights from Butcher array (without the first empty row).
a - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Internal weights Butcher array.
a - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Internal weights Butcher array.
a - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Internal weights Butcher array.
a - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Internal weights from Butcher array (without the first empty row).
a - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Internal weights Butcher array.
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.
a1 - Variable in class org.apache.commons.math.geometry.RotationOrder
  Axis of the first rotation.
a2 - Variable in class org.apache.commons.math.geometry.RotationOrder
  Axis of the second rotation.
a3 - Variable in class org.apache.commons.math.geometry.RotationOrder
  Axis of the third rotation.
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() - 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.
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
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(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(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(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute the sum of this and v.
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(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(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
  Adds 1 to the frequency count for v.
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() - 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
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.
alpha - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
  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, 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.
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`.
atan() - Method in class org.apache.commons.math.complex.Complex
  Compute the inverse tangent of this complex number.

## B

b - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Propagation weights Butcher array.
b - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  External weights for the high order method from Butcher array.
b - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Propagation weights Butcher array.
b - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Propagation weights Butcher array.
b - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Propagation weights Butcher array.
b - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  External weights for the high order method from Butcher array.
b - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Propagation weights 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.distribution.WeibullDistributionImpl
  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) - Constructor for class org.apache.commons.math.distribution.BetaDistributionImpl
  Build a new instance.
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.
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.
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.
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.MathException
  Builds a message string by from a pattern and its arguments.
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
  Members of c[] are called centers of the Newton polynomial.
c - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
  Time steps Butcher array.
c - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
  Time steps from Butcher array (without the first zero).
c - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
  Time steps Butcher array.
c - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
  Time steps Butcher array.
c - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
  Time steps Butcher array.
c - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
  Time steps from Butcher array (without the first zero).
c - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
  Time steps Butcher array.
c - Static variable in class org.apache.commons.math.optimization.univariate.BrentOptimizer
  Golden section.
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.
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[], boolean) - 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) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
  Throws DimensionMismatchException if dimension != k.
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.ArrayFieldVector
  Check if an index is valid.
checkIndex(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
  Check if an index is valid.
checkIndex(int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.
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
checkUpperTriangular(RealMatrix, double) - Static method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Check if a matrix is upper-triangular.
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(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.OpenMapRealVector
  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
  Create a Chi-Squared distribution with the given degrees of freedom.
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 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.
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 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.
columnDimension - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
  Number of columns of the matrix.
columnDimension - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
  column dimension
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.
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.
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(double, double) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
  Computes binStats
computeBinStats(double, double) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
  Compute bin stats.
computeBinStats(double, double) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
  Computes binStats
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.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.
computeGershgorinCircles() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Compute the Gershgorin circles for all rows.
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.
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.
computeShiftIncrement(int, int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Compute the shift increment as an estimate of the smallest eigenvalue.
computeSplits() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Compute splitting points.
computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
  Computes sampleStats
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
  Computes sampleStats
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.
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.AbstractLinearOptimizer
  Linear constraints.
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.
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.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.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.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[], int) - 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() - Method in class org.apache.commons.math.complex.Complex
  Compute the cosine of this complex number.
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.
countEigenValues(double, int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Count the number of realEigenvalues below a point.
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.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.
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() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Decompose a tridiagonal symmetric matrix.
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_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_BANDWIDTH - Static variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Default value of the bandwidth parameter.
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.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_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.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_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
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 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
  Return 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
  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
  Return 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
  Return the probability density for a particular point.
density(P) - Method in interface org.apache.commons.math.distribution.HasDensity
  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
  Return 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).
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.
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
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.
dimension1 - Variable in exception org.apache.commons.math.DimensionMismatchException
  First dimension.
dimension2 - Variable in exception org.apache.commons.math.DimensionMismatchException
  Second dimension.
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.
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.
discardArtificialVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Removes the phase 1 objective function and artificial variables from this tableau.
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.
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(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.
dMin - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Minimal value on current state of the diagonal.
dMin1 - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Minimal value on current state of the diagonal, excluding last element.
dMin2 - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Minimal value on current state of the diagonal, excluding last two elements.
dN - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Last value on current state of the diagonal.
dN1 - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Last but one value on current state of the diagonal.
dN2 - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Last but two on current state of the diagonal.
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(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(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Compute the dot product.
dotProduct(double[]) - 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.
dqd(int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Perform a dqd step.
dqds(int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Perform a dqds step, using current shift increment.
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.
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[], 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
  Exeption 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.

## 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(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(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 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 given tridiagonal symmetric 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.
eigenvaluesRange(int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Compute an interval containing all realEigenvalues of a block.
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.
eMin - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Min value of off-diagonal elements in current segment.
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
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.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.
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[], 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 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[], 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[], 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[], 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) - 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.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.
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.
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.
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.
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 = mu
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.
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.general.AbstractLeastSquaresOptimizer
  Objective function.
f - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Objective function.
f - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Linear objective function.
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
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.
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, double, double) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns the index of the bin to which the given value belongs
findEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find the realEigenvalues.
findEigenvector(double, double[], double[]) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find an eigenvector corresponding to an eigenvalue, using bidiagonals.
findEigenVectors() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find eigenvectors.
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.
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.
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.
flipIfWarranted(int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Flip qd array if warranted.
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`.
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.LeastSquaresConverter
  Underlying vectorial 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 - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Shift ratio with respect to dMin used when tType == 6.
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.
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.
GAUSSIAN_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Gaussian random deviates with mean = mu, std dev = sigma
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.
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.
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.
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 - Static variable in class org.apache.commons.math.stat.StatUtils
  geometric mean
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 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.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.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.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()``
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.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.
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.
getEpsilon() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Get the tolerance for having a value considered zero.
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 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 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.
getGamma() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the Gamma distribution.
getGenerator() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
  Get the underlying normalized components generator.
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.
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.
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.
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.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.
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.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.ArrayRealVector
  Returns the L1 norm of the vector.
getL1Norm() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.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.ArrayRealVector
  Returns the L∞ norm of the vector.
getLInfNorm() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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 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
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.
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(Locale) - Method in exception org.apache.commons.math.MathRuntimeException
  Gets the message in a specified locale.
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
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.
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.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 class org.apache.commons.math.linear.OpenMapRealVector
  Returns the L2 norm of the vector.
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.
getNormalizedConstraints() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get new versions of the constraints which have positive right hand sides.
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.
getNumVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Get the number of 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.
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(int, SimplexTableau) - 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.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`
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.
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.
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 interface org.apache.commons.math.ode.ODEIntegrator
  Get all the step handlers that have been added to the integrator.
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.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.
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
goalType - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
  Type of optimization.
GoalType - Enum in org.apache.commons.math.optimization
  Goal type for an optimization problem.
GoalType() - Constructor for enum org.apache.commons.math.optimization.GoalType
goalType - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
  Type of optimization goal: either `GoalType.MAXIMIZE` or `GoalType.MINIMIZE`.
goodStep(int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Perform one "good" dqd/dqds step.
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.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.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.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
  Interface that signals that a distribution can compute the probability density function for a particular point.
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.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.
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.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.
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.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''' ...
initialize() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
  Puts the tableau in proper form by zeroing out the artificial variables in the objective function via elementary row operations.
initializeArrays() - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
  Initialize the integrator internal arrays.
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.
initialSplits(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Perform two iterations with Li's tests for initial splits.
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 providng 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
  The only instance.
INSTANCE - Static variable in class org.apache.commons.math.util.BigRealField.LazyHolder
  Cached field instance.
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(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.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[]) - 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.NevilleInterpolator
  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
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.
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.
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.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(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Returns whether the problem is at an optimal state.
isPhase1Solved(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
  Checks whether Phase 1 is solved.
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.
isZero(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Determine if this value is zero.
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.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.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`.
ldlTDecomposition(double, int, int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Decompose the shifted tridiagonal matrix T-λI as LDLT.
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.
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` and `LoessInterpolator.DEFAULT_ROBUSTNESS_ITERS` robustness iterations.
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.
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`.
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).
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`.
lowerSpectra - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Lower bound of spectra.
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.
mainBidiagonal - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Main diagonal of the bidiagonal matrix.
mainTridiagonal - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Main diagonal of the tridiagonal matrix.
map - Variable in class org.apache.commons.math.util.TransformerMap
  The internal Map.
mapAbs() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.abs(double)` function to each entry.
mapAbs() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.abs(double)` function to each entry.
mapAbsToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.acos(double)` function to each entry.
mapAcos() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.acos(double)` function to each entry.
mapAcosToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map an addition operation to each entry.
mapAdd(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  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(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.ArrayRealVector
  Map the `Math.asin(double)` function to each entry.
mapAsin() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.asin(double)` function to each entry.
mapAsinToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.atan(double)` function to each entry.
mapAtan() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.atan(double)` function to each entry.
mapAtanToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCbrt() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.cbrt(double)` function to each entry.
mapCbrtToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.ceil(double)` function to each entry.
mapCeil() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.ceil(double)` function to each entry.
mapCeilToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.cos(double)` function to each entry.
mapCos() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.cosh(double)` function to each entry.
mapCosh() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.cosh(double)` function to each entry.
mapCoshToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.cos(double)` function to each entry.
mapCosToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a division operation to each entry.
mapDivide(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  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 class org.apache.commons.math.linear.OpenMapRealVector
  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(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 class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.exp(double)` function to each entry.
mapExp() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpm1() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.expm1(double)` function to each entry.
mapExpm1ToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.exp(double)` function to each entry.
mapExpToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.floor(double)` function to each entry.
mapFloor() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.floor(double)` function to each entry.
mapFloorToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayFieldVector
  Map the 1/x function to each entry.
mapInv() - Method in class org.apache.commons.math.linear.ArrayRealVector
  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 class org.apache.commons.math.linear.OpenMapRealVector
  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.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 class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.log(double)` function to each entry.
mapLog() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.log10(double)` function to each entry.
mapLog10() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.log10(double)` function to each entry.
mapLog10ToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.log1p(double)` function to each entry.
mapLog1p() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.log1p(double)` function to each entry.
mapLog1pToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.log(double)` function to each entry.
mapLogToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a multiplication operation to each entry.
mapMultiply(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  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 class org.apache.commons.math.linear.OpenMapRealVector
  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(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 class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map a power operation to each entry.
mapPow(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map a power operation to each entry.
mapPowToSelf(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.rint(double)` function to each entry.
mapRint() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.rint(double)` function to each entry.
mapRintToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.signum(double)` function to each entry.
mapSignum() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.signum(double)` function to each entry.
mapSignumToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.sin(double)` function to each entry.
mapSin() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinh() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.sinh(double)` function to each entry.
mapSinhToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.sin(double)` function to each entry.
mapSinToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSqrt() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.sqrt(double)` function to each entry.
mapSqrtToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
  Map a subtraction operation to each entry.
mapSubtract(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
  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 class org.apache.commons.math.linear.OpenMapRealVector
  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(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 class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.tan(double)` function to each entry.
mapTan() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanh() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.tanh(double)` function to each entry.
mapTanhToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.tan(double)` function to each entry.
mapTanToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.
mapUlp() - Method in class org.apache.commons.math.linear.ArrayRealVector
  Map the `Math.ulp(double)` function to each entry.
mapUlp() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.ArrayRealVector
  Map the `Math.ulp(double)` function to each entry.
mapUlpToSelf() - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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
  Default 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 - 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.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.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 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.
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 - 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.
minPivot - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Minimum pivot in the Sturm sequence.
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".
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(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.
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.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() - 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.
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(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`.
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.
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.
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.
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.
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.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() - 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.
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.
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.
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.
ODEIntegrator - Interface in org.apache.commons.math.ode
  This interface defines the common parts shared by integrators for first and second order differential equations.
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.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.
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.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.
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(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Optimized method to compute the outer product.
outerProduct(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  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.

## 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
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`.
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.
pingPong - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Shift within qd array for ping-pong implementation.
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, NormalDistribution) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Create a new Poisson distribution with the given the mean.
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.
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.
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
process1RowBlock(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find eigenvalue in a block with 1 row.
process2RowsBlock(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find realEigenvalues in a block with 2 rows.
process3RowsBlock(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find realEigenvalues in a block with 3 rows.
processGeneralBlock(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Find realEigenvalues using dqd/dqds algorithms.
prod - Static variable in class org.apache.commons.math.stat.StatUtils
  prod
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(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.
progressiveQuotientDifferenceWithShift(double[], double[], double) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Decompose matrix LDLT - λ I as U-D-U-T.
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.
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.
qMax - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Max value of diagonal elements in current segment.
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
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.
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.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.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.
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(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.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.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.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_STATE - Static variable in interface org.apache.commons.math.ode.events.EventHandler
  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.
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.
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.AbstractLinearOptimizer
  Whether to restrict the variables to non-negative values.
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.
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
roundUnscaled(double, double, int) - Static method in class org.apache.commons.math.util.MathUtils
  Round the given non-negative, value to the "nearest" integer.
rowDimension - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
  Number of rows of the matrix.
rowDimension - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
  row dimension
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.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
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(UnivariateRealFunction, double, double, int) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
  Sample the given univariate real function on the given interval.
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.linear.BigMatrixImpl
  Deprecated. BigDecimal scale
scale - Variable in class org.apache.commons.math.optimization.LeastSquaresConverter
  Optional scaling matrix (weight and correlations) for the residuals.
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.
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.
secondaryBidiagonal - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Secondary diagonal of the bidiagonal matrix.
secondaryTridiagonal - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Secondary diagonal of the tridiagonal matrix.
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.
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
  Serializtion 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.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(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.
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
  Modify the shape parameter, alpha.
setAlpha(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Modify the shape parameter, alpha.
setAlpha(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Modify the shape parameter, alpha.
setAlpha(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
  Modify the shape parameter, beta.
setBeta(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
  Modify the shape parameter, beta.
setBeta(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Modify the scale parameter, beta.
setBeta(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.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
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
  Modify the degrees of freedom.
setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Modify the degrees of freedom.
setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.TDistribution
  Modify the degrees of freedom.
setDegreesOfFreedom(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
  Modify the denominator degrees of freedom.
setDenominatorDegreesOfFreedom(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.
setEpsilon(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
  Set the tolerance for having a value considered zero.
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
  Set the exponent characterising the distribution.
setExponent(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
  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.
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.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 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
  Modify the mean.
setMean(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Modify the mean.
setMean(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Modify the mean.
setMean(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Modify the mean.
setMean(double) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Set the mean for the distribution.
setMean(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Set the Poisson mean for the distribution.
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.
setMedian(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
  Modify the median.
setMedian(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Modify the median.
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
  Modify the normal distribution used to compute normal approximations.
setNumberOfElements(int) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
  Set the number of elements (e.g.
setNumberOfElements(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
  Modify the number of successes.
setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the number of successes.
setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.PascalDistribution
  Change the number of successes for this distribution.
setNumberOfSuccesses(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
  Change the number of trials for this distribution.
setNumberOfTrials(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
  Modify the numerator degrees of freedom.
setNumeratorDegreesOfFreedom(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.
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
  Modify the population size.
setPopulationSize(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
  Change the probability of success for this distribution.
setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Change the probability of success for this distribution.
setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.PascalDistribution
  Change the probability of success for this distribution.
setProbabilityOfSuccess(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.
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
  Modify the sample size.
setSampleSize(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
  Modify the scale parameter.
setScale(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
  Modify the scale parameter.
setScale(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
  Modify the scale parameter.
setScale(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
  Modify the scale parameter.
setScale(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Deprecated. Sets the scale for division operations.
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
  Modify the shape parameter.
setShape(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
  Modify the standard deviation.
setStandardDeviation(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, 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.
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`
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.
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.linear.EigenDecompositionImpl
  Current shift.
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
sigmaLow - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Low part of the current shift.
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`.
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() - 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 Singular Value Decomposition of a matrix.
SingularValueDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.SingularValueDecompositionImpl
  Calculates the 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.
singularValues - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  Singular values.
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[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
  Compute a loess fit on the data at the original abscissae.
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).
solveUpperTriangular(RealMatrix, RealVector) - Static method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
  Uses back substitution to solve the system
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.
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
splitTolerance - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Split tolerance.
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.
squaredSecondary - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Squared secondary diagonal of the tridiagonal matrix.
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.
staticA - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Internal weights Butcher array.
staticA - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Internal weights Butcher array.
staticA - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Internal weights Butcher array.
staticB - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Propagation weights Butcher array.
staticB - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Propagation weights Butcher array.
staticB - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Propagation weights Butcher array.
staticC - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
  Time steps Butcher array.
staticC - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
  Time steps Butcher array.
staticC - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Time steps Butcher array.
staticE - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
  Error weights Butcher array.
stationaryQuotientDifferenceWithShift(double[], double[], double) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Decompose matrix LDLT - λ I as L+D+L+T.
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.
StepInterpolator - Interface in org.apache.commons.math.ode.sampling
  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.
StoppingCondition - Interface in org.apache.commons.math.genetics
  Algorithm used to determine when to stop evolution.
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(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(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.
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 - Static variable in class org.apache.commons.math.stat.StatUtils
  sumLog
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 - Static variable in class org.apache.commons.math.stat.StatUtils
  sumSq
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() - Method in class org.apache.commons.math.complex.Complex
  Compute the tangent of this complex number.
tanh() - Method in class org.apache.commons.math.complex.Complex
  Compute the hyperbolic tangent of this complex number.
target - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
  Target value for the objective functions at optimum.
tau - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Shift increment to apply.
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) - 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.
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
tMq - Static variable in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  First Gill coefficient.
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.
TOLERANCE - Static variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Tolerance.
TOLERANCE_2 - Static variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Squared tolerance.
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.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.
tPq - Static variable in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
  Second Gill coefficient.
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.linear.SingularValueDecompositionImpl
  Transformer to bidiagonal.
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.
tType - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Type of the last dqds shift.
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_PI - Static variable in class org.apache.commons.math.util.MathUtils
  2 π.
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

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 = mu
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.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.
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.
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[], 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]
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.
updateSigma(double) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
  Update sigma.
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).
upperSpectra - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Upper bound of spectra.
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.
uT - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  UT matrix of the decomposition.

## V

v - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
  V matrix of the decomposition.
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[]) - 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.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.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]).
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.
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.
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.
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.general.AbstractLeastSquaresOptimizer
  Weight for the least squares cost computation.
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
work - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
  Work array for all decomposition algorithms.
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.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.

## X

x - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
  Interpolating points (abscissas) and the function values at these points.
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
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
  Interpolating points (abscissas) and the function values at these points.
y - Variable in class org.apache.commons.math.geometry.Vector3D
  Ordinate.
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
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.
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.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.
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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