001 /*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements. See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License. You may obtain a copy of the License at
008 *
009 * http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017
018 package org.apache.commons.math.distribution;
019
020 /**
021 * Test cases for ChiSquareDistribution.
022 * Extends ContinuousDistributionAbstractTest. See class javadoc for
023 * ContinuousDistributionAbstractTest for details.
024 *
025 * @version $Revision: 762087 $ $Date: 2009-04-05 10:20:18 -0400 (Sun, 05 Apr 2009) $
026 */
027 public class ChiSquareDistributionTest extends ContinuousDistributionAbstractTest {
028
029 /**
030 * Constructor for ChiSquareDistributionTest.
031 * @param name
032 */
033 public ChiSquareDistributionTest(String name) {
034 super(name);
035 }
036
037 //-------------- Implementations for abstract methods -----------------------
038
039 /** Creates the default continuous distribution instance to use in tests. */
040 @Override
041 public ContinuousDistribution makeDistribution() {
042 return new ChiSquaredDistributionImpl(5.0);
043 }
044
045 /** Creates the default cumulative probability distribution test input values */
046 @Override
047 public double[] makeCumulativeTestPoints() {
048 // quantiles computed using R version 1.8.1 (linux version)
049 return new double[] {0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
050 20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d};
051 }
052
053 /** Creates the default cumulative probability density test expected values */
054 @Override
055 public double[] makeCumulativeTestValues() {
056 return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
057 0.990d, 0.975d, 0.950d, 0.900d};
058 }
059
060 /** Creates the default inverse cumulative probability test input values */
061 @Override
062 public double[] makeInverseCumulativeTestPoints() {
063 return new double[] {0, 0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
064 0.990d, 0.975d, 0.950d, 0.900d, 1};
065 }
066
067 /** Creates the default inverse cumulative probability density test expected values */
068 @Override
069 public double[] makeInverseCumulativeTestValues() {
070 return new double[] {0, 0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
071 20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d,
072 Double.POSITIVE_INFINITY};
073 }
074
075 // --------------------- Override tolerance --------------
076 @Override
077 protected void setUp() throws Exception {
078 super.setUp();
079 setTolerance(5e-6);
080 }
081
082 //---------------------------- Additional test cases -------------------------
083
084 public void testSmallDf() throws Exception {
085 setDistribution(new ChiSquaredDistributionImpl(0.1d));
086 setTolerance(1E-4);
087 // quantiles computed using R version 1.8.1 (linux version)
088 setCumulativeTestPoints(new double[] {1.168926E-60, 1.168926E-40, 1.063132E-32,
089 1.144775E-26, 1.168926E-20, 5.472917, 2.175255, 1.13438,
090 0.5318646, 0.1526342});
091 setInverseCumulativeTestValues(getCumulativeTestPoints());
092 setInverseCumulativeTestPoints(getCumulativeTestValues());
093 verifyCumulativeProbabilities();
094 verifyInverseCumulativeProbabilities();
095 }
096
097 public void testDfAccessors() {
098 ChiSquaredDistribution distribution = (ChiSquaredDistribution) getDistribution();
099 assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
100 distribution.setDegreesOfFreedom(4d);
101 assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
102 try {
103 distribution.setDegreesOfFreedom(0d);
104 fail("Expecting IllegalArgumentException for df = 0");
105 } catch (IllegalArgumentException ex) {
106 // expected
107 }
108 }
109
110 public void testDensity() {
111 double[] x = new double[]{-0.1, 1e-6, 0.5, 1, 2, 5};
112 //R 2.5: print(dchisq(x, df=1), digits=10)
113 checkDensity(1, x, new double[]{0.00000000000, 398.94208093034, 0.43939128947, 0.24197072452, 0.10377687436, 0.01464498256});
114 //R 2.5: print(dchisq(x, df=0.1), digits=10)
115 checkDensity(0.1, x, new double[]{0.000000000e+00, 2.486453997e+04, 7.464238732e-02, 3.009077718e-02, 9.447299159e-03, 8.827199396e-04});
116 //R 2.5: print(dchisq(x, df=2), digits=10)
117 checkDensity(2, x, new double[]{0.00000000000, 0.49999975000, 0.38940039154, 0.30326532986, 0.18393972059, 0.04104249931});
118 //R 2.5: print(dchisq(x, df=10), digits=10)
119 checkDensity(10, x, new double[]{0.000000000e+00, 1.302082682e-27, 6.337896998e-05, 7.897534632e-04, 7.664155024e-03, 6.680094289e-02});
120 }
121
122 private void checkDensity(double df, double[] x, double[] expected) {
123 ChiSquaredDistribution d = new ChiSquaredDistributionImpl(df);
124 for (int i = 0; i < x.length; i++) {
125 assertEquals(expected[i], d.density(x[i]), 1e-5);
126 }
127 }
128
129 }