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: 620312 $ $Date: 2008-02-10 12:28:59 -0700 (Sun, 10 Feb 2008) $ 34 * @since 1.2 35 * 36 */ 37 38 public interface Estimator { 39 40 /** 41 * Solve an estimation problem. 42 * 43 * <p>The method should set the parameters of the problem to several 44 * trial values until it reaches convergence. If this method returns 45 * normally (i.e. without throwing an exception), then the best 46 * estimate of the parameters can be retrieved from the problem 47 * itself, through the {@link EstimationProblem#getAllParameters 48 * EstimationProblem.getAllParameters} method.</p> 49 * 50 * @param problem estimation problem to solve 51 * @exception EstimationException if the problem cannot be solved 52 * 53 */ 54 public void estimate(EstimationProblem problem) 55 throws EstimationException; 56 57 /** 58 * Get the Root Mean Square value. 59 * Get the Root Mean Square value, i.e. the root of the arithmetic 60 * mean of the square of all weighted residuals. This is related to the 61 * criterion that is minimized by the estimator as follows: if 62 * <em>c</em> is the criterion, and <em>n</em> is the number of 63 * measurements, then the RMS is <em>sqrt (c/n)</em>. 64 * @see #guessParametersErrors(EstimationProblem) 65 * 66 * @param problem estimation problem 67 * @return RMS value 68 */ 69 public double getRMS(EstimationProblem problem); 70 71 /** 72 * Get the covariance matrix of estimated parameters. 73 * @param problem estimation problem 74 * @return covariance matrix 75 * @exception EstimationException if the covariance matrix 76 * cannot be computed (singular problem) 77 */ 78 public double[][] getCovariances(EstimationProblem problem) 79 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 public double[] guessParametersErrors(EstimationProblem problem) 89 throws EstimationException; 90 91 }