Modified to extend ContinuousDistributionAbstractTest, improved coverage.
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141247 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz
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@ -16,77 +16,74 @@
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package org.apache.commons.math.distribution;
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import junit.framework.TestCase;
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/**
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* @version $Revision: 1.14 $ $Date: 2004/05/23 21:34:19 $
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* Test cases for ChiSquareDistribution.
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* Extends ContinuousDistributionAbstractTest. See class javadoc for
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* ContinuousDistributionAbstractTest for details.
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*
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* @version $Revision: 1.15 $ $Date: 2004/05/29 22:52:44 $
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*/
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public class ChiSquareDistributionTest extends TestCase {
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private ChiSquaredDistribution chiSquare;
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public class ChiSquareDistributionTest extends ContinuousDistributionAbstractTest {
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/**
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* Constructor for ChiSquareDistributionTest.
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* @param name
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*/
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public ChiSquareDistributionTest(String name) {
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super(name);
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}
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/*
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* @see TestCase#setUp()
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*/
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protected void setUp() throws Exception {
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super.setUp();
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chiSquare = DistributionFactory.newInstance().createChiSquareDistribution(5.0);
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}
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/*
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* @see TestCase#tearDown()
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*/
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protected void tearDown() throws Exception {
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chiSquare = null;
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super.tearDown();
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}
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public void testLowerTailProbability() throws Exception {
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testProbability( .210, .001);
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testProbability( .554, .010);
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testProbability( .831, .025);
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testProbability(1.145, .050);
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testProbability(1.610, .100);
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/**
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* Constructor for ChiSquareDistributionTest.
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* @param name
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*/
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public ChiSquareDistributionTest(String name) {
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super(name);
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}
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//-------------- Implementations for abstract methods -----------------------
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/** Creates the default continuous distribution instance to use in tests. */
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public ContinuousDistribution makeDistribution() {
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return DistributionFactory.newInstance().createChiSquareDistribution(5.0);
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}
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/** Creates the default cumulative probability distribution test input values */
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public double[] makeCumulativeTestPoints() {
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// quantiles computed using R version 1.8.1 (linux version)
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return new double[] {0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
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20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d};
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}
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/** Creates the default cumulative probability density test expected values */
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public double[] makeCumulativeTestValues() {
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return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
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0.990d, 0.975d, 0.950d, 0.900d};
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}
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// --------------------- Override tolerance --------------
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protected void setup() throws Exception {
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super.setUp();
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setTolerance(1E-6);
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}
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public void testUpperTailProbability() throws Exception {
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testProbability(20.515, .999);
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testProbability(15.086, .990);
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testProbability(12.833, .975);
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testProbability(11.070, .950);
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testProbability( 9.236, .900);
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//---------------------------- Additional test cases -------------------------
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public void testSmallDf() throws Exception {
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setDistribution(DistributionFactory.newInstance().createChiSquareDistribution(0.1d));
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setTolerance(1E-4);
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// quantiles computed using R version 1.8.1 (linux version)
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setCumulativeTestPoints(new double[] {1.168926E-60, 1.168926E-40, 1.063132E-32,
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1.144775E-26, 1.168926E-20, 5.472917, 2.175255, 1.13438,
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0.5318646, 0.1526342});
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setInverseCumulativeTestValues(getCumulativeTestPoints());
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verifyCumulativeProbabilities();
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verifyInverseCumulativeProbabilities();
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}
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public void testLowerTailValues() throws Exception {
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testValue(.001, .210);
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testValue(.010, .554);
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testValue(.025, .831);
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testValue(.050, 1.145);
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testValue(.100, 1.610);
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}
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public void testDfAccessors() {
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ChiSquaredDistribution distribution = (ChiSquaredDistribution) getDistribution();
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assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
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distribution.setDegreesOfFreedom(4d);
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assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
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try {
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distribution.setDegreesOfFreedom(0d);
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fail("Expecting IllegalArgumentException for df = 0");
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} catch (IllegalArgumentException ex) {
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// expected
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}
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}
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public void testUpperTailValues() throws Exception {
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testValue(.999, 20.515);
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testValue(.990, 15.086);
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testValue(.975, 12.833);
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testValue(.950, 11.070);
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testValue(.900, 9.236);
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}
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private void testProbability(double x, double expected) throws Exception {
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double actual = chiSquare.cumulativeProbability(x);
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assertEquals("probability for " + x, expected, actual, 10e-4);
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}
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private void testValue(double p, double expected) throws Exception {
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double actual = chiSquare.inverseCumulativeProbability(p);
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assertEquals("value for " + p, expected, actual, 10e-4);
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}
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}
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