| /* |
| * 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.statistics.distribution; |
| |
| import org.junit.jupiter.api.Assertions; |
| import org.junit.jupiter.api.BeforeEach; |
| import org.junit.jupiter.api.Test; |
| |
| /** |
| * Test cases for BinomialDistribution. Extends DiscreteDistributionAbstractTest. |
| * See class javadoc for DiscreteDistributionAbstractTest for details. |
| */ |
| class BinomialDistributionTest extends DiscreteDistributionAbstractTest { |
| |
| //---------------------- Override tolerance -------------------------------- |
| |
| @BeforeEach |
| void customSetUp() { |
| setTolerance(1e-12); |
| } |
| |
| //-------------- Implementations for abstract methods ---------------------- |
| |
| @Override |
| public DiscreteDistribution makeDistribution() { |
| return new BinomialDistribution(10, 0.70); |
| } |
| |
| @Override |
| public int[] makeProbabilityTestPoints() { |
| return new int[] {-1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}; |
| } |
| |
| @Override |
| public double[] makeProbabilityTestValues() { |
| // Reference values are from R, version 2.15.3. |
| return new double[] {0d, 0.0000059049d, 0.000137781d, 0.0014467005, |
| 0.009001692, 0.036756909, 0.1029193452, 0.200120949, 0.266827932, |
| 0.2334744405, 0.121060821, 0.0282475249, 0d}; |
| } |
| |
| @Override |
| public int[] makeCumulativeTestPoints() { |
| return makeProbabilityTestPoints(); |
| } |
| |
| @Override |
| public double[] makeCumulativeTestValues() { |
| // Reference values are from R, version 2.15.3. |
| return new double[] {0d, 5.9049e-06, 0.0001436859, 0.0015903864, 0.0105920784, 0.0473489874, |
| 0.1502683326, 0.3503892816, 0.6172172136, 0.8506916541, 0.9717524751, 1d, 1d}; |
| } |
| |
| @Override |
| public double[] makeInverseCumulativeTestPoints() { |
| return new double[] {0, 0.001d, 0.010d, 0.025d, 0.050d, 0.100d, |
| 0.999d, 0.990d, 0.975d, 0.950d, 0.900d, 1d}; |
| } |
| |
| @Override |
| public int[] makeInverseCumulativeTestValues() { |
| return new int[] {0, 2, 3, 4, 5, 5, 10, 10, 10, 9, 9, 10}; |
| } |
| |
| //-------------------- Additional test cases ------------------------------- |
| |
| /** Test case n = 10, p = 0.3. */ |
| @Test |
| void testSmallPValue() { |
| final BinomialDistribution dist = new BinomialDistribution(10, 0.3); |
| setDistribution(dist); |
| // computed using R version 3.4.4 |
| setCumulativeTestValues(new double[] {0.00000000000000000000, 0.02824752489999998728, 0.14930834590000002793, |
| 0.38278278639999974153, 0.64961071840000017552, 0.84973166740000016794, 0.95265101260000006889, |
| 0.98940792160000001765, 0.99840961360000002323, 0.99985631409999997654, 0.99999409509999992451, |
| 1.00000000000000000000, 1.00000000000000000000}); |
| setProbabilityTestValues(new double[] {0.0000000000000000000e+00, 2.8247524899999980341e-02, |
| 1.2106082099999991575e-01, 2.3347444049999999116e-01, 2.6682793199999993439e-01, 2.0012094900000007569e-01, |
| 1.0291934520000002584e-01, 3.6756909000000004273e-02, 9.0016919999999864960e-03, 1.4467005000000008035e-03, |
| 1.3778099999999990615e-04, 5.9048999999999949131e-06, 0.0000000000000000000e+00}); |
| setInverseCumulativeTestValues(new int[] {0, 0, 0, 0, 1, 1, 8, 7, 6, 5, 5, 10}); |
| verifyProbabilities(); |
| verifyLogProbabilities(); |
| verifyCumulativeProbabilities(); |
| verifySurvivalProbability(); |
| verifySurvivalAndCumulativeProbabilityComplement(); |
| verifyInverseCumulativeProbabilities(); |
| } |
| |
| /** Test degenerate case p = 0 */ |
| @Test |
| void testDegenerate0() { |
| final BinomialDistribution dist = new BinomialDistribution(5, 0.0d); |
| setDistribution(dist); |
| setCumulativeTestPoints(new int[] {-1, 0, 1, 5, 10}); |
| setCumulativeTestValues(new double[] {0d, 1d, 1d, 1d, 1d}); |
| setProbabilityTestPoints(new int[] {-1, 0, 1, 10, 11}); |
| setProbabilityTestValues(new double[] {0d, 1d, 0d, 0d, 0d}); |
| setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d}); |
| setInverseCumulativeTestValues(new int[] {0, 0}); |
| verifyProbabilities(); |
| verifyLogProbabilities(); |
| verifyCumulativeProbabilities(); |
| verifySurvivalProbability(); |
| verifySurvivalAndCumulativeProbabilityComplement(); |
| verifyInverseCumulativeProbabilities(); |
| Assertions.assertEquals(0, dist.getSupportLowerBound()); |
| Assertions.assertEquals(0, dist.getSupportUpperBound()); |
| } |
| |
| /** Test degenerate case p = 1 */ |
| @Test |
| void testDegenerate1() { |
| final BinomialDistribution dist = new BinomialDistribution(5, 1.0d); |
| setDistribution(dist); |
| setCumulativeTestPoints(new int[] {-1, 0, 1, 2, 5, 10}); |
| setCumulativeTestValues(new double[] {0d, 0d, 0d, 0d, 1d, 1d}); |
| setProbabilityTestPoints(new int[] {-1, 0, 1, 2, 5, 10}); |
| setProbabilityTestValues(new double[] {0d, 0d, 0d, 0d, 1d, 0d}); |
| setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d}); |
| setInverseCumulativeTestValues(new int[] {5, 5}); |
| verifyProbabilities(); |
| verifyLogProbabilities(); |
| verifyCumulativeProbabilities(); |
| verifySurvivalProbability(); |
| verifySurvivalAndCumulativeProbabilityComplement(); |
| verifyInverseCumulativeProbabilities(); |
| Assertions.assertEquals(5, dist.getSupportLowerBound()); |
| Assertions.assertEquals(5, dist.getSupportUpperBound()); |
| } |
| |
| /** Test degenerate case n = 0 */ |
| @Test |
| void testDegenerate2() { |
| final BinomialDistribution dist = new BinomialDistribution(0, 0.01d); |
| setDistribution(dist); |
| setCumulativeTestPoints(new int[] {-1, 0, 1, 2, 5, 10}); |
| setCumulativeTestValues(new double[] {0d, 1d, 1d, 1d, 1d, 1d}); |
| setProbabilityTestPoints(new int[] {-1, 0, 1, 2, 5, 10}); |
| setProbabilityTestValues(new double[] {0d, 1d, 0d, 0d, 0d, 0d}); |
| setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d}); |
| setInverseCumulativeTestValues(new int[] {0, 0}); |
| verifyProbabilities(); |
| verifyLogProbabilities(); |
| verifyCumulativeProbabilities(); |
| verifySurvivalProbability(); |
| verifySurvivalAndCumulativeProbabilityComplement(); |
| verifyInverseCumulativeProbabilities(); |
| Assertions.assertEquals(0, dist.getSupportLowerBound()); |
| Assertions.assertEquals(0, dist.getSupportUpperBound()); |
| } |
| |
| @Test |
| void testParameterAccessors() { |
| for (final int n : new int[] {11, 42, 999}) { |
| for (final double p : new double[] {0.1, 0.456, 0.999}) { |
| final BinomialDistribution dist = new BinomialDistribution(n, p); |
| Assertions.assertEquals(n, dist.getNumberOfTrials()); |
| Assertions.assertEquals(p, dist.getProbabilityOfSuccess()); |
| } |
| } |
| } |
| |
| @Test |
| void testConstructorPrecondition1() { |
| Assertions.assertThrows(DistributionException.class, () -> new BinomialDistribution(-1, 0.1)); |
| } |
| |
| @Test |
| void testConstructorPrecondition2() { |
| Assertions.assertThrows(DistributionException.class, () -> new BinomialDistribution(10, -0.1)); |
| } |
| |
| @Test |
| void testConstructorPrecondition3() { |
| Assertions.assertThrows(DistributionException.class, () -> new BinomialDistribution(10, 1.1)); |
| } |
| |
| @Test |
| void testMoments() { |
| final double tol = 1e-9; |
| BinomialDistribution dist; |
| |
| dist = new BinomialDistribution(10, 0.5); |
| Assertions.assertEquals(10d * 0.5d, dist.getMean(), tol); |
| Assertions.assertEquals(10d * 0.5d * 0.5d, dist.getVariance(), tol); |
| |
| dist = new BinomialDistribution(30, 0.3); |
| Assertions.assertEquals(30d * 0.3d, dist.getMean(), tol); |
| Assertions.assertEquals(30d * 0.3d * (1d - 0.3d), dist.getVariance(), tol); |
| } |
| |
| @Test |
| void testMath718() { |
| // for large trials the evaluation of ContinuedFraction was inaccurate |
| // do a sweep over several large trials to test if the current implementation is |
| // numerically stable. |
| |
| for (int trials = 500000; trials < 20000000; trials += 100000) { |
| final BinomialDistribution dist = new BinomialDistribution(trials, 0.5); |
| final int p = dist.inverseCumulativeProbability(0.5); |
| Assertions.assertEquals(trials / 2, p); |
| } |
| } |
| |
| @Test |
| void testHighPrecisionCumulativeProbabilities() { |
| // computed using R version 3.4.4 |
| setDistribution(new BinomialDistribution(100, 0.99)); |
| setCumulativePrecisionTestPoints(new int[] {82, 81}); |
| setCumulativePrecisionTestValues(new double[] {1.4061271955993513664e-17, 6.1128083336354843707e-19}); |
| verifyCumulativeProbabilityPrecision(); |
| } |
| |
| @Test |
| void testHighPrecisionSurvivalProbabilities() { |
| // computed using R version 3.4.4 |
| setDistribution(new BinomialDistribution(100, 0.01)); |
| setSurvivalPrecisionTestPoints(new int[] {18, 19}); |
| setSurvivalPrecisionTestValues(new double[] {6.1128083336353977038e-19, 2.4944165604029235392e-20}); |
| verifySurvivalProbabilityPrecision(); |
| } |
| } |