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

See Also:

EstimationProblem

Method Summary

Modifier and Type	Method and Description
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)