Interface Estimator
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- All Known Implementing Classes:
AbstractEstimator
,GaussNewtonEstimator
,LevenbergMarquardtEstimator
@Deprecated public interface Estimator
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.generalThis 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 11:36:08 +0200 (dim. 06 sept. 2009) $
- See Also:
EstimationProblem
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Method Summary
All Methods Instance Methods Abstract Methods Deprecated Methods Modifier and Type Method 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.
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Method Detail
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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
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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)
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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)
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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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