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 }