1   /*
2    * Copyright 2003-2005 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  package org.apache.commons.math.distribution;
17  
18  /**
19   * Test cases for TDistribution.
20   * Extends ContinuousDistributionAbstractTest.  See class javadoc for
21   * ContinuousDistributionAbstractTest for details.
22   *
23   * @version $Revision: 201916 $ $Date: 2005-06-26 15:25:41 -0700 (Sun, 26 Jun 2005) $
24   */
25  public class TDistributionTest extends ContinuousDistributionAbstractTest {
26  
27      /**
28       * Constructor for TDistributionTest.
29       * @param name
30       */
31      public TDistributionTest(String name) {
32          super(name);
33      }
34  
35  //-------------- Implementations for abstract methods -----------------------
36  
37      /** Creates the default continuous distribution instance to use in tests. */
38      public ContinuousDistribution makeDistribution() {
39          return DistributionFactory.newInstance().createTDistribution(5.0);
40      }
41  
42      /** Creates the default cumulative probability distribution test input values */
43      public double[] makeCumulativeTestPoints() {
44          // quantiles computed using R version 1.8.1 (linux version)
45          return new double[] {-5.89343,-3.36493, -2.570582, -2.015048,
46              -1.475884, 0.0, 5.89343, 3.36493, 2.570582,
47              2.015048, 1.475884};
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, 0.5d, 0.999d,
53                  0.990d, 0.975d, 0.950d, 0.900d};
54      }
55  
56      // --------------------- Override tolerance  --------------
57      protected void setup() throws Exception {
58          super.setUp();
59          setTolerance(1E-6);
60      }
61  
62      //---------------------------- Additional test cases -------------------------
63      /**
64       * @see <a href="http://issues.apache.org/bugzilla/show_bug.cgi?id=27243">
65       *      Bug report that prompted this unit test.</a>
66       */
67      public void testCumulativeProbabilityAgaintStackOverflow() throws Exception {
68          TDistributionImpl td = new TDistributionImpl(5.);
69          double est;
70          est = td.cumulativeProbability(.1);
71          est = td.cumulativeProbability(.01);
72      }
73  
74      public void testSmallDf() throws Exception {
75          setDistribution(DistributionFactory.newInstance().createTDistribution(1d));
76          setTolerance(1E-4);
77          // quantiles computed using R version 1.8.1 (linux version)
78          setCumulativeTestPoints(new double[] {-318.3088, -31.82052, -12.70620, -6.313752,
79              -3.077684, 0.0, 318.3088, 31.82052, 12.70620,
80              6.313752, 3.077684});
81          setInverseCumulativeTestValues(getCumulativeTestPoints());
82          verifyCumulativeProbabilities();
83          verifyInverseCumulativeProbabilities();
84      }
85  
86      public void testInverseCumulativeProbabilityExtremes() throws Exception {
87          setInverseCumulativeTestPoints(new double[] {0, 1});
88          setInverseCumulativeTestValues(
89                  new double[] {Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY});
90          verifyInverseCumulativeProbabilities();
91      }
92  
93      public void testDfAccessors() {
94          TDistribution distribution = (TDistribution) getDistribution();
95          assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
96          distribution.setDegreesOfFreedom(4d);
97          assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
98          try {
99              distribution.setDegreesOfFreedom(0d);
100             fail("Expecting IllegalArgumentException for df = 0");
101         } catch (IllegalArgumentException ex) {
102             // expected
103         }
104     }
105 
106 }