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Java > Open Source Codes > org > apache > commons > math > distribution > ChiSquareDistributionTest


1 /*
2  * Copyright 2003-2004 The Apache Software Foundation.
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16
17 package org.apache.commons.math.distribution;
18
19 /**
20  * Test cases for ChiSquareDistribution.
21  * Extends ContinuousDistributionAbstractTest. See class javadoc for
22  * ContinuousDistributionAbstractTest for details.
23  *
24  * @version $Revision$ $Date: 2005-02-26 05:11:52 -0800 (Sat, 26 Feb 2005) $
25  */
26 public class ChiSquareDistributionTest extends ContinuousDistributionAbstractTest {
27     
28     /**
29      * Constructor for ChiSquareDistributionTest.
30      * @param name
31      */
32     public ChiSquareDistributionTest(String JavaDoc name) {
33         super(name);
34     }
35     
36     //-------------- Implementations for abstract methods -----------------------
37
38     /** Creates the default continuous distribution instance to use in tests. */
39     public ContinuousDistribution makeDistribution() {
40         return DistributionFactory.newInstance().createChiSquareDistribution(5.0);
41     }
42     
43     /** Creates the default cumulative probability distribution test input values */
44     public double[] makeCumulativeTestPoints() {
45         // quantiles computed using R version 1.8.1 (linux version)
46 return new double[] {0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
47                 20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d};
48     }
49     
50     /** Creates the default cumulative probability density test expected values */
51     public double[] makeCumulativeTestValues() {
52         return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
53                 0.990d, 0.975d, 0.950d, 0.900d};
54     }
55     
56     /** Creates the default inverse cumulative probability test input values */
57     public double[] makeInverseCumulativeTestPoints() {
58         return new double[] {0, 0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
59                 0.990d, 0.975d, 0.950d, 0.900d, 1};
60     }
61     
62     /** Creates the default inverse cumulative probability density test expected values */
63     public double[] makeInverseCumulativeTestValues() {
64         return new double[] {0, 0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
65                 20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d,
66                 Double.POSITIVE_INFINITY};
67     }
68     
69  // --------------------- Override tolerance --------------
70 protected void setup() throws Exception JavaDoc {
71         super.setUp();
72         setTolerance(1E-6);
73     }
74
75  //---------------------------- Additional test cases -------------------------
76
77     public void testSmallDf() throws Exception JavaDoc {
78         setDistribution(DistributionFactory.newInstance().createChiSquareDistribution(0.1d));
79         setTolerance(1E-4);
80         // quantiles computed using R version 1.8.1 (linux version)
81 setCumulativeTestPoints(new double[] {1.168926E-60, 1.168926E-40, 1.063132E-32,
82                 1.144775E-26, 1.168926E-20, 5.472917, 2.175255, 1.13438,
83                 0.5318646, 0.1526342});
84         setInverseCumulativeTestValues(getCumulativeTestPoints());
85         setInverseCumulativeTestPoints(getCumulativeTestValues());
86         verifyCumulativeProbabilities();
87         verifyInverseCumulativeProbabilities();
88     }
89     
90     public void testDfAccessors() {
91         ChiSquaredDistribution distribution = (ChiSquaredDistribution) getDistribution();
92         assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
93         distribution.setDegreesOfFreedom(4d);
94         assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
95         try {
96             distribution.setDegreesOfFreedom(0d);
97             fail("Expecting IllegalArgumentException for df = 0");
98         } catch (IllegalArgumentException JavaDoc ex) {
99             // expected
100 }
101     }
102     
103 }
104
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