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 ChiSquareDistribution.
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 ChiSquareDistributionTest extends ContinuousDistributionAbstractTest {
028        
029        /**
030         * Constructor for ChiSquareDistributionTest.
031         * @param name
032         */
033        public ChiSquareDistributionTest(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 ChiSquaredDistributionImpl(5.0);
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[] {0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d, 
050                    20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d};
051        }
052        
053        /** Creates the default cumulative probability density test expected values */
054        @Override
055        public double[] makeCumulativeTestValues() {
056            return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
057                    0.990d, 0.975d, 0.950d, 0.900d}; 
058        }
059        
060        /** Creates the default inverse cumulative probability test input values */
061        @Override
062        public double[] makeInverseCumulativeTestPoints() {
063            return new double[] {0, 0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
064                    0.990d, 0.975d, 0.950d, 0.900d, 1};     
065        }
066        
067        /** Creates the default inverse cumulative probability density test expected values */
068        @Override
069        public double[] makeInverseCumulativeTestValues() {
070            return new double[] {0, 0.210216d, 0.5542981d, 0.8312116d, 1.145476d, 1.610308d, 
071                    20.51501d, 15.08627d, 12.83250d, 11.07050d, 9.236357d, 
072                    Double.POSITIVE_INFINITY};
073        }
074        
075     // --------------------- Override tolerance  --------------
076        @Override
077        protected void setUp() throws Exception {
078            super.setUp();
079            setTolerance(5e-6);
080        }
081    
082     //---------------------------- Additional test cases -------------------------
083        
084        public void testSmallDf() throws Exception {
085            setDistribution(new ChiSquaredDistributionImpl(0.1d));
086            setTolerance(1E-4);
087            // quantiles computed using R version 1.8.1 (linux version)
088            setCumulativeTestPoints(new double[] {1.168926E-60, 1.168926E-40, 1.063132E-32, 
089                    1.144775E-26, 1.168926E-20, 5.472917, 2.175255, 1.13438, 
090                    0.5318646, 0.1526342});
091            setInverseCumulativeTestValues(getCumulativeTestPoints());
092            setInverseCumulativeTestPoints(getCumulativeTestValues());
093            verifyCumulativeProbabilities();
094            verifyInverseCumulativeProbabilities();
095        }
096        
097        public void testDfAccessors() {
098            ChiSquaredDistribution distribution = (ChiSquaredDistribution) getDistribution();
099            assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
100            distribution.setDegreesOfFreedom(4d);
101            assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
102            try {
103                distribution.setDegreesOfFreedom(0d);
104                fail("Expecting IllegalArgumentException for df = 0");
105            } catch (IllegalArgumentException ex) {
106                // expected
107            }
108        }
109    
110        public void testDensity() {
111            double[] x = new double[]{-0.1, 1e-6, 0.5, 1, 2, 5};
112            //R 2.5: print(dchisq(x, df=1), digits=10)
113            checkDensity(1, x, new double[]{0.00000000000, 398.94208093034, 0.43939128947, 0.24197072452, 0.10377687436, 0.01464498256});
114            //R 2.5: print(dchisq(x, df=0.1), digits=10)
115            checkDensity(0.1, x, new double[]{0.000000000e+00, 2.486453997e+04, 7.464238732e-02, 3.009077718e-02, 9.447299159e-03, 8.827199396e-04});
116            //R 2.5: print(dchisq(x, df=2), digits=10)
117            checkDensity(2, x, new double[]{0.00000000000, 0.49999975000, 0.38940039154, 0.30326532986, 0.18393972059, 0.04104249931});
118            //R 2.5: print(dchisq(x, df=10), digits=10)
119            checkDensity(10, x, new double[]{0.000000000e+00, 1.302082682e-27, 6.337896998e-05, 7.897534632e-04, 7.664155024e-03, 6.680094289e-02});
120        }
121    
122        private void checkDensity(double df, double[] x, double[] expected) {
123            ChiSquaredDistribution d = new ChiSquaredDistributionImpl(df);
124            for (int i = 0; i < x.length; i++) {
125                assertEquals(expected[i], d.density(x[i]), 1e-5);
126            }
127        }
128    
129    }