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 GammaDistribution. 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 GammaDistributionTest extends ContinuousDistributionAbstractTest { 028 029 /** 030 * Constructor for GammaDistributionTest. 031 * @param name 032 */ 033 public GammaDistributionTest(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 GammaDistributionImpl(4d, 2d); 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[] {0.8571048, 1.646497, 2.179731, 2.732637, 050 3.489539, 26.12448, 20.09024, 17.53455, 051 15.50731, 13.36157}; 052 } 053 054 /** Creates the default cumulative probability density test expected values */ 055 @Override 056 public double[] makeCumulativeTestValues() { 057 return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d, 058 0.990d, 0.975d, 0.950d, 0.900d}; 059 } 060 061 // --------------------- Override tolerance -------------- 062 @Override 063 protected void setUp() throws Exception { 064 super.setUp(); 065 setTolerance(6e-6); 066 } 067 068 //---------------------------- Additional test cases ------------------------- 069 public void testParameterAccessors() { 070 GammaDistribution distribution = (GammaDistribution) getDistribution(); 071 assertEquals(4d, distribution.getAlpha(), 0); 072 distribution.setAlpha(3d); 073 assertEquals(3d, distribution.getAlpha(), 0); 074 assertEquals(2d, distribution.getBeta(), 0); 075 distribution.setBeta(4d); 076 assertEquals(4d, distribution.getBeta(), 0); 077 try { 078 distribution.setAlpha(0d); 079 fail("Expecting IllegalArgumentException for alpha = 0"); 080 } catch (IllegalArgumentException ex) { 081 // expected 082 } 083 try { 084 distribution.setBeta(0d); 085 fail("Expecting IllegalArgumentException for beta = 0"); 086 } catch (IllegalArgumentException ex) { 087 // expected 088 } 089 } 090 091 public void testProbabilities() throws Exception { 092 testProbability(-1.000, 4.0, 2.0, .0000); 093 testProbability(15.501, 4.0, 2.0, .9499); 094 testProbability(0.504, 4.0, 1.0, .0018); 095 testProbability(10.011, 1.0, 2.0, .9933); 096 testProbability(5.000, 2.0, 2.0, .7127); 097 } 098 099 public void testValues() throws Exception { 100 testValue(15.501, 4.0, 2.0, .9499); 101 testValue(0.504, 4.0, 1.0, .0018); 102 testValue(10.011, 1.0, 2.0, .9933); 103 testValue(5.000, 2.0, 2.0, .7127); 104 } 105 106 private void testProbability(double x, double a, double b, double expected) throws Exception { 107 GammaDistribution distribution = new GammaDistributionImpl( a, b ); 108 double actual = distribution.cumulativeProbability(x); 109 assertEquals("probability for " + x, expected, actual, 10e-4); 110 } 111 112 private void testValue(double expected, double a, double b, double p) throws Exception { 113 GammaDistribution distribution = new GammaDistributionImpl( a, b ); 114 double actual = distribution.inverseCumulativeProbability(p); 115 assertEquals("critical value for " + p, expected, actual, 10e-4); 116 } 117 118 public void testDensity() { 119 double[] x = new double[]{-0.1, 1e-6, 0.5, 1, 2, 5}; 120 // R2.5: print(dgamma(x, shape=1, rate=1), digits=10) 121 checkDensity(1, 1, x, new double[]{0.000000000000, 0.999999000001, 0.606530659713, 0.367879441171, 0.135335283237, 0.006737946999}); 122 // R2.5: print(dgamma(x, shape=2, rate=1), digits=10) 123 checkDensity(2, 1, x, new double[]{0.000000000000, 0.000000999999, 0.303265329856, 0.367879441171, 0.270670566473, 0.033689734995}); 124 // R2.5: print(dgamma(x, shape=4, rate=1), digits=10) 125 checkDensity(4, 1, x, new double[]{0.000000000e+00, 1.666665000e-19, 1.263605541e-02, 6.131324020e-02, 1.804470443e-01, 1.403738958e-01}); 126 // R2.5: print(dgamma(x, shape=4, rate=10), digits=10) 127 checkDensity(4, 10, x, new double[]{0.000000000e+00, 1.666650000e-15, 1.403738958e+00, 7.566654960e-02, 2.748204830e-05, 4.018228850e-17}); 128 // R2.5: print(dgamma(x, shape=.1, rate=10), digits=10) 129 checkDensity(0.1, 10, x, new double[]{0.000000000e+00, 3.323953832e+04, 1.663849010e-03, 6.007786726e-06, 1.461647647e-10, 5.996008322e-24}); 130 // R2.5: print(dgamma(x, shape=.1, rate=20), digits=10) 131 checkDensity(0.1, 20, x, new double[]{0.000000000e+00, 3.562489883e+04, 1.201557345e-05, 2.923295295e-10, 3.228910843e-19, 1.239484589e-45}); 132 // R2.5: print(dgamma(x, shape=.1, rate=4), digits=10) 133 checkDensity(0.1, 4, x, new double[]{0.000000000e+00, 3.032938388e+04, 3.049322494e-02, 2.211502311e-03, 2.170613371e-05, 5.846590589e-11}); 134 // R2.5: print(dgamma(x, shape=.1, rate=1), digits=10) 135 checkDensity(0.1, 1, x, new double[]{0.000000000e+00, 2.640334143e+04, 1.189704437e-01, 3.866916944e-02, 7.623306235e-03, 1.663849010e-04}); 136 } 137 138 private void checkDensity(double alpha, double rate, double[] x, double[] expected) { 139 GammaDistribution d = new GammaDistributionImpl(alpha, 1 / rate); 140 for (int i = 0; i < x.length; i++) { 141 assertEquals(expected[i], d.density(x[i]), 1e-5); 142 } 143 } 144 145 public void testInverseCumulativeProbabilityExtremes() throws Exception { 146 setInverseCumulativeTestPoints(new double[] {0, 1}); 147 setInverseCumulativeTestValues(new double[] {0, Double.POSITIVE_INFINITY}); 148 verifyInverseCumulativeProbabilities(); 149 } 150 }