/*
 * 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 $Revision$ $Date$
 * @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
	 *
	 */
	public 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
	 */
	public 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)
	 */
	public 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
	 */
	public double[] guessParametersErrors(EstimationProblem problem) throws EstimationException;

}
