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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math.estimation;
/**
* This interface represents solvers for estimation problems.
*
* <p>The classes which are devoted to solve estimation problems
* should implement this interface. The problems which can be handled
* should implement the {@link EstimationProblem} interface which
* gather all the information needed by the solver.</p>
*
* <p>The interface is composed only of the {@link #estimate estimate}
* method.</p>
*
* @see EstimationProblem
*
* @version $Revision: 811786 $ $Date: 2009-09-06 11:36:08 +0200 (dim. 06 sept. 2009) $
* @since 1.2
* @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 {
/**
* Solve an estimation problem.
*
* <p>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 {@link EstimationProblem#getAllParameters
* EstimationProblem.getAllParameters} method.</p>
*
* @param problem estimation problem to solve
* @exception EstimationException if the problem cannot be solved
*
*/
void estimate(EstimationProblem problem) throws EstimationException;
/**
* 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
* <em>c</em> is the criterion, and <em>n</em> is the number of
* measurements, then the RMS is <em>sqrt (c/n)</em>.
* @see #guessParametersErrors(EstimationProblem)
*
* @param problem estimation problem
* @return RMS value
*/
double getRMS(EstimationProblem problem);
/**
* Get the covariance matrix of estimated parameters.
* @param problem estimation problem
* @return covariance matrix
* @exception EstimationException if the covariance matrix
* cannot be computed (singular problem)
*/
double[][] getCovariances(EstimationProblem problem) throws EstimationException;
/**
* Guess the errors in estimated parameters.
* @see #getRMS(EstimationProblem)
* @param problem estimation problem
* @return errors in estimated parameters
* @exception EstimationException if the error cannot be guessed
*/
double[] guessParametersErrors(EstimationProblem problem) throws EstimationException;
}
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