## org.apache.commons.math.estimation
Interface Estimator

All Known Implementing Classes:
  AbstractEstimator, GaussNewtonEstimator, LevenbergMarquardtEstimator

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

    @Deprecated
    public interface Estimator

This interface represents solvers for estimation problems.

The classes which are devoted to solve estimation problems should implement this interface. The problems which can be handled should implement the `EstimationProblem` interface which gather all the information needed by the solver.

The interface is composed only of the `estimate` method.

Since:
  1.2
Version:
  $Revision: 811786 $ $Date: 2009-09-06 05:36:08 -0400 (Sun, 06 Sep 2009) $
See Also:
  `EstimationProblem`

Method Summary
`void` `estimate(EstimationProblem problem)` Deprecated. Solve an estimation problem.
`double[][]` `getCovariances(EstimationProblem problem)` Deprecated. Get the covariance matrix of estimated parameters.
`double` `getRMS(EstimationProblem problem)` Deprecated. Get the Root Mean Square value.
`double[]` `guessParametersErrors(EstimationProblem problem)` Deprecated. Guess the errors in estimated parameters.

Method Detail

### estimate

    void estimate(EstimationProblem problem)
                  throws EstimationException

  Deprecated.
  Solve an estimation problem.

  The method should set the parameters of the problem to several trial values until it reaches convergence. If this method returns normally (i.e. without throwing an exception), then the best estimate of the parameters can be retrieved from the problem itself, through the `EstimationProblem.getAllParameters` method.

  Parameters:
    `problem` - estimation problem to solve
  Throws:
    `EstimationException` - if the problem cannot be solved

### getRMS

    double getRMS(EstimationProblem problem)

  Deprecated.
  Get the Root Mean Square value. Get the Root Mean Square value, i.e. the root of the arithmetic mean of the square of all weighted residuals. This is related to the criterion that is minimized by the estimator as follows: if c is the criterion, and n is the number of measurements, then the RMS is sqrt (c/n).

  Parameters:
    `problem` - estimation problem
  Returns:
    RMS value
  See Also:
    `guessParametersErrors(EstimationProblem)`

### getCovariances

    double[][] getCovariances(EstimationProblem problem)
                              throws EstimationException

  Deprecated.
  Get the covariance matrix of estimated parameters.

  Parameters:
    `problem` - estimation problem
  Returns:
    covariance matrix
  Throws:
    `EstimationException` - if the covariance matrix cannot be computed (singular problem)

### guessParametersErrors

    double[] guessParametersErrors(EstimationProblem problem)
                                   throws EstimationException

  Deprecated.
  Guess the errors in estimated parameters.

  Parameters:
    `problem` - estimation problem
  Returns:
    errors in estimated parameters
  Throws:
    `EstimationException` - if the error cannot be guessed
  See Also:
    `getRMS(EstimationProblem)`

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