Modified to extent ContinuousDistrbutionAbstractTest. Improved coverage.

git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141249 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2004-05-30 01:39:33 +00:00
parent dc8569711f
commit 1d5a4e2d3d
1 changed files with 64 additions and 51 deletions

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@ -15,73 +15,86 @@
*/
package org.apache.commons.math.distribution;
import junit.framework.TestCase;
/**
* @version $Revision: 1.13 $ $Date: 2004/05/23 21:34:19 $
* Test cases for FDistribution.
* Extends ContinuousDistributionAbstractTest. See class javadoc for
* ContinuousDistributionAbstractTest for details.
*
* @version $Revision: 1.14 $ $Date: 2004/05/30 01:39:33 $
*/
public class FDistributionTest extends TestCase {
private FDistribution f;
public class FDistributionTest extends ContinuousDistributionAbstractTest {
/**
* Constructor for ChiSquareDistributionTest.
* Constructor for FDistributionTest.
* @param name
*/
public FDistributionTest(String name) {
super(name);
}
/*
* @see TestCase#setUp()
*/
protected void setUp() throws Exception {
//-------------- Implementations for abstract methods -----------------------
/** Creates the default continuous distribution instance to use in tests. */
public ContinuousDistribution makeDistribution() {
return DistributionFactory.newInstance().createFDistribution(5.0, 6.0);
}
/** Creates the default cumulative probability distribution test input values */
public double[] makeCumulativeTestPoints() {
// quantiles computed using R version 1.8.1 (linux version)
return new double[] {0.03468084d ,0.09370091d, 0.1433137d,
0.2020084d, 0.2937283d, 20.80266d, 8.745895d, 5.987565d,
4.387374d, 3.107512d};
}
/** Creates the default cumulative probability density test expected values */
public double[] makeCumulativeTestValues() {
return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
0.990d, 0.975d, 0.950d, 0.900d};
}
// --------------------- Override tolerance --------------
protected void setup() throws Exception {
super.setUp();
f = DistributionFactory.newInstance().createFDistribution(5.0, 6.0);
setTolerance(1E-6);
}
/*
* @see TestCase#tearDown()
*/
protected void tearDown() throws Exception {
f = null;
super.tearDown();
//---------------------------- Additional test cases -------------------------
public void testCumulativeProbabilityExtremes() throws Exception {
setCumulativeTestPoints(new double[] {-2, 0});
setCumulativeTestValues(new double[] {0, 0});
verifyCumulativeProbabilities();
}
public void testLowerTailProbability() throws Exception {
testProbability(1.0 / 10.67, .010);
testProbability(1.0 / 6.98, .025);
testProbability(1.0 / 4.95, .050);
testProbability(1.0 / 3.40, .100);
public void testInverseCumulativeProbabilityExtremes() throws Exception {
//TODO: decide what to do about p = 1. This currently blows up the solver.
setInverseCumulativeTestPoints(new double[] {0});
setInverseCumulativeTestValues(new double[] {0});
verifyInverseCumulativeProbabilities();
}
public void testDfAccessors() {
FDistribution distribution = (FDistribution) getDistribution();
assertEquals(5d, distribution.getNumeratorDegreesOfFreedom(), Double.MIN_VALUE);
distribution.setNumeratorDegreesOfFreedom(4d);
assertEquals(4d, distribution.getNumeratorDegreesOfFreedom(), Double.MIN_VALUE);
assertEquals(6d, distribution.getDenominatorDegreesOfFreedom(), Double.MIN_VALUE);
distribution.setDenominatorDegreesOfFreedom(4d);
assertEquals(4d, distribution.getDenominatorDegreesOfFreedom(), Double.MIN_VALUE);
try {
distribution.setNumeratorDegreesOfFreedom(0d);
fail("Expecting IllegalArgumentException for df = 0");
} catch (IllegalArgumentException ex) {
// expected
}
try {
distribution.setDenominatorDegreesOfFreedom(0d);
fail("Expecting IllegalArgumentException for df = 0");
} catch (IllegalArgumentException ex) {
// expected
}
}
public void testUpperTailProbability() throws Exception {
testProbability(8.75, .990);
testProbability(5.99, .975);
testProbability(4.39, .950);
testProbability(3.11, .900);
}
public void testLowerTailValues() throws Exception {
testValue(1.0 / 10.67, .010);
testValue(1.0 / 6.98, .025);
testValue(1.0 / 4.95, .050);
testValue(1.0 / 3.40, .100);
}
public void testUpperTailValues() throws Exception {
testValue(8.75, .990);
testValue(5.99, .975);
testValue(4.39, .950);
testValue(3.11, .900);
}
private void testProbability(double x, double expected) throws Exception {
double actual = f.cumulativeProbability(x);
assertEquals("probability for " + x, expected, actual, 1e-3);
}
private void testValue(double expected, double p) throws Exception {
double actual = f.inverseCumulativeProbability(p);
assertEquals("value for " + p, expected, actual, 1e-2);
}
}