/*
* Copyright 2003-2004 The Apache Software Foundation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math.distribution;
/**
* Test cases for ChiSquareDistribution.
* Extends ContinuousDistributionAbstractTest. See class javadoc for
* ContinuousDistributionAbstractTest for details.
*
* @version $Revision: 1.16 $ $Date: 2004/07/24 20:43:29 $
*/
public class ChiSquareDistributionTest extends ContinuousDistributionAbstractTest {
/**
* Constructor for ChiSquareDistributionTest.
* @param name
*/
public ChiSquareDistributionTest(String name) {
super(name);
}
//-------------- Implementations for abstract methods -----------------------
/** Creates the default continuous distribution instance to use in tests. */
public ContinuousDistribution makeDistribution() {
return DistributionFactory.newInstance().createChiSquareDistribution(5.0);
}
/** 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[] {0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d};
}
/** 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};
}
/** Creates the default inverse cumulative probability test input values */
public double[] makeInverseCumulativeTestPoints() {
return new double[] {0, 0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
0.990d, 0.975d, 0.950d, 0.900d, 1};
}
/** Creates the default inverse cumulative probability density test expected values */
public double[] makeInverseCumulativeTestValues() {
return new double[] {0, 0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d,
20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d,
Double.POSITIVE_INFINITY};
}
// --------------------- Override tolerance --------------
protected void setup() throws Exception {
super.setUp();
setTolerance(1E-6);
}
//---------------------------- Additional test cases -------------------------
public void testSmallDf() throws Exception {
setDistribution(DistributionFactory.newInstance().createChiSquareDistribution(0.1d));
setTolerance(1E-4);
// quantiles computed using R version 1.8.1 (linux version)
setCumulativeTestPoints(new double[] {1.168926E-60, 1.168926E-40, 1.063132E-32,
1.144775E-26, 1.168926E-20, 5.472917, 2.175255, 1.13438,
0.5318646, 0.1526342});
setInverseCumulativeTestValues(getCumulativeTestPoints());
setInverseCumulativeTestPoints(getCumulativeTestValues());
verifyCumulativeProbabilities();
verifyInverseCumulativeProbabilities();
}
public void testDfAccessors() {
ChiSquaredDistribution distribution = (ChiSquaredDistribution) getDistribution();
assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
distribution.setDegreesOfFreedom(4d);
assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
try {
distribution.setDegreesOfFreedom(0d);
fail("Expecting IllegalArgumentException for df = 0");
} catch (IllegalArgumentException ex) {
// expected
}
}
}
This source code is protected by copyright!
more..
