Commons Math example source code file (FDistributionTest.java)

This example Commons Math source code file (FDistributionTest.java) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" ^TM.

Java - Commons Math tags/keywords

continuousdistributionabstracttest, exception, exception, expecting, fdistribution, fdistribution, fdistributiontest, illegalargumentexception, illegalargumentexception, override, override

The Commons Math FDistributionTest.java source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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 FDistribution.
 * Extends ContinuousDistributionAbstractTest.  See class javadoc for
 * ContinuousDistributionAbstractTest for details.
 *
 * @version $Revision: 924362 $ $Date: 2010-03-17 12:45:31 -0400 (Wed, 17 Mar 2010) $
 */
public class FDistributionTest extends ContinuousDistributionAbstractTest {

    /**
     * Constructor for FDistributionTest.
     * @param name
     */
    public FDistributionTest(String name) {
        super(name);
    }

    //-------------- Implementations for abstract methods -----------------------

    /** Creates the default continuous distribution instance to use in tests. */
    @Override
    public FDistribution makeDistribution() {
        return new FDistributionImpl(5.0, 6.0);
    }

    /** Creates the default cumulative probability distribution test input values */
    @Override
    public double[] makeCumulativeTestPoints() {
        // quantiles computed using R version 2.9.2
        return new double[] {0.0346808448626, 0.0937009113303, 0.143313661184, 0.202008445998, 0.293728320107,
                20.8026639595, 8.74589525602, 5.98756512605, 4.38737418741, 3.10751166664};
    }

    /** Creates the default cumulative probability density test expected values */
    @Override
    public double[] makeCumulativeTestValues() {
        return new double[] {0.001, 0.01, 0.025, 0.05, 0.1, 0.999, 0.990, 0.975, 0.950, 0.900};
    }

    /** Creates the default probability density test expected values */
    @Override
    public double[] makeDensityTestValues() {
        return new double[] {0.0689156576706, 0.236735653193, 0.364074131941, 0.481570789649, 0.595880479994,
                0.000133443915657, 0.00286681303403, 0.00969192007502, 0.0242883861471, 0.0605491314658};
    }

    // --------------------- Override tolerance  --------------
    @Override
    protected void setUp() throws Exception {
        super.setUp();
        setTolerance(1e-9);
    }

    //---------------------------- Additional test cases -------------------------

    public void testCumulativeProbabilityExtremes() throws Exception {
        setCumulativeTestPoints(new double[] {-2, 0});
        setCumulativeTestValues(new double[] {0, 0});
        verifyCumulativeProbabilities();
    }

    public void testInverseCumulativeProbabilityExtremes() throws Exception {
        setInverseCumulativeTestPoints(new double[] {0, 1});
        setInverseCumulativeTestValues(new double[] {0, Double.POSITIVE_INFINITY});
        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 testLargeDegreesOfFreedom() throws Exception {
        org.apache.commons.math.distribution.FDistributionImpl fd =
            new org.apache.commons.math.distribution.FDistributionImpl(
                100000., 100000.);
        double p = fd.cumulativeProbability(.999);
        double x = fd.inverseCumulativeProbability(p);
        assertEquals(.999, x, 1.0e-5);
    }

    public void testSmallDegreesOfFreedom() throws Exception {
        org.apache.commons.math.distribution.FDistributionImpl fd =
            new org.apache.commons.math.distribution.FDistributionImpl(
                1.0, 1.0);
        double p = fd.cumulativeProbability(0.975);
        double x = fd.inverseCumulativeProbability(p);
        assertEquals(0.975, x, 1.0e-5);

        fd.setDenominatorDegreesOfFreedom(2.0);
        p = fd.cumulativeProbability(0.975);
        x = fd.inverseCumulativeProbability(p);
        assertEquals(0.975, x, 1.0e-5);
    }

}