1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 18 package org.apache.commons.math.estimation; 19 20 /** 21 * This interface represents solvers for estimation problems. 22 * 23 * <p>The classes which are devoted to solve estimation problems 24 * should implement this interface. The problems which can be handled 25 * should implement the {@link EstimationProblem} interface which 26 * gather all the information needed by the solver.</p> 27 * 28 * <p>The interface is composed only of the {@link #estimate estimate} 29 * method.</p> 30 * 31 * @see EstimationProblem 32 * 33 * @version $Revision: 811786 $ $Date: 2009-09-06 11:36:08 +0200 (dim. 06 sept. 2009) $ 34 * @since 1.2 35 * @deprecated as of 2.0, everything in package org.apache.commons.math.estimation has 36 * been deprecated and replaced by package org.apache.commons.math.optimization.general 37 * 38 */ 39 @Deprecated 40 public interface Estimator { 41 42 /** 43 * Solve an estimation problem. 44 * 45 * <p>The method should set the parameters of the problem to several 46 * trial values until it reaches convergence. If this method returns 47 * normally (i.e. without throwing an exception), then the best 48 * estimate of the parameters can be retrieved from the problem 49 * itself, through the {@link EstimationProblem#getAllParameters 50 * EstimationProblem.getAllParameters} method.</p> 51 * 52 * @param problem estimation problem to solve 53 * @exception EstimationException if the problem cannot be solved 54 * 55 */ 56 void estimate(EstimationProblem problem) throws EstimationException; 57 58 /** 59 * Get the Root Mean Square value. 60 * Get the Root Mean Square value, i.e. the root of the arithmetic 61 * mean of the square of all weighted residuals. This is related to the 62 * criterion that is minimized by the estimator as follows: if 63 * <em>c</em> is the criterion, and <em>n</em> is the number of 64 * measurements, then the RMS is <em>sqrt (c/n)</em>. 65 * @see #guessParametersErrors(EstimationProblem) 66 * 67 * @param problem estimation problem 68 * @return RMS value 69 */ 70 double getRMS(EstimationProblem problem); 71 72 /** 73 * Get the covariance matrix of estimated parameters. 74 * @param problem estimation problem 75 * @return covariance matrix 76 * @exception EstimationException if the covariance matrix 77 * cannot be computed (singular problem) 78 */ 79 double[][] getCovariances(EstimationProblem problem) throws EstimationException; 80 81 /** 82 * Guess the errors in estimated parameters. 83 * @see #getRMS(EstimationProblem) 84 * @param problem estimation problem 85 * @return errors in estimated parameters 86 * @exception EstimationException if the error cannot be guessed 87 */ 88 double[] guessParametersErrors(EstimationProblem problem) throws EstimationException; 89 90 } 91
