1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 package org.apache.commons.math.distribution; 18 19 import java.io.Serializable; 20 21 import org.apache.commons.math.MathException; 22 import org.apache.commons.math.special.Beta; 23 import org.apache.commons.math.util.MathUtils; 24 25 /** 26 * The default implementation of {@link BinomialDistribution}. 27 * 28 * @version $Revision: 617953 $ $Date: 2008-02-02 22:54:00 -0700 (Sat, 02 Feb 2008) $ 29 */ 30 public class BinomialDistributionImpl 31 extends AbstractIntegerDistribution 32 implements BinomialDistribution, Serializable { 33 34 /** Serializable version identifier */ 35 private static final long serialVersionUID = 6751309484392813623L; 36 37 /** The number of trials. */ 38 private int numberOfTrials; 39 40 /** The probability of success. */ 41 private double probabilityOfSuccess; 42 43 /** 44 * Create a binomial distribution with the given number of trials and 45 * probability of success. 46 * @param trials the number of trials. 47 * @param p the probability of success. 48 */ 49 public BinomialDistributionImpl(int trials, double p) { 50 super(); 51 setNumberOfTrials(trials); 52 setProbabilityOfSuccess(p); 53 } 54 55 /** 56 * Access the number of trials for this distribution. 57 * @return the number of trials. 58 */ 59 public int getNumberOfTrials() { 60 return numberOfTrials; 61 } 62 63 /** 64 * Access the probability of success for this distribution. 65 * @return the probability of success. 66 */ 67 public double getProbabilityOfSuccess() { 68 return probabilityOfSuccess; 69 } 70 71 /** 72 * Change the number of trials for this distribution. 73 * @param trials the new number of trials. 74 * @throws IllegalArgumentException if <code>trials</code> is not a valid 75 * number of trials. 76 */ 77 public void setNumberOfTrials(int trials) { 78 if (trials < 0) { 79 throw new IllegalArgumentException("number of trials must be non-negative."); 80 } 81 numberOfTrials = trials; 82 } 83 84 /** 85 * Change the probability of success for this distribution. 86 * @param p the new probability of success. 87 * @throws IllegalArgumentException if <code>p</code> is not a valid 88 * probability. 89 */ 90 public void setProbabilityOfSuccess(double p) { 91 if (p < 0.0 || p > 1.0) { 92 throw new IllegalArgumentException("probability of success must be between 0.0 and 1.0, inclusive."); 93 } 94 probabilityOfSuccess = p; 95 } 96 97 /** 98 * Access the domain value lower bound, based on <code>p</code>, used to 99 * bracket a PDF root. 100 * 101 * @param p the desired probability for the critical value 102 * @return domain value lower bound, i.e. 103 * P(X < <i>lower bound</i>) < <code>p</code> 104 */ 105 protected int getDomainLowerBound(double p) { 106 return -1; 107 } 108 109 /** 110 * Access the domain value upper bound, based on <code>p</code>, used to 111 * bracket a PDF root. 112 * 113 * @param p the desired probability for the critical value 114 * @return domain value upper bound, i.e. 115 * P(X < <i>upper bound</i>) > <code>p</code> 116 */ 117 protected int getDomainUpperBound(double p) { 118 return getNumberOfTrials(); 119 } 120 121 /** 122 * For this distribution, X, this method returns P(X ≤ x). 123 * @param x the value at which the PDF is evaluated. 124 * @return PDF for this distribution. 125 * @throws MathException if the cumulative probability can not be 126 * computed due to convergence or other numerical errors. 127 */ 128 public double cumulativeProbability(int x) throws MathException { 129 double ret; 130 if (x < 0) { 131 ret = 0.0; 132 } else if (x >= getNumberOfTrials()) { 133 ret = 1.0; 134 } else { 135 ret = 136 1.0 - Beta.regularizedBeta( 137 getProbabilityOfSuccess(), 138 x + 1.0, 139 getNumberOfTrials() - x); 140 } 141 return ret; 142 } 143 144 /** 145 * For this disbution, X, this method returns P(X = x). 146 * 147 * @param x the value at which the PMF is evaluated. 148 * @return PMF for this distribution. 149 */ 150 public double probability(int x) { 151 double ret; 152 if (x < 0 || x > getNumberOfTrials()) { 153 ret = 0.0; 154 } else { 155 ret = MathUtils.binomialCoefficientDouble( 156 getNumberOfTrials(), x) * 157 Math.pow(getProbabilityOfSuccess(), x) * 158 Math.pow(1.0 - getProbabilityOfSuccess(), 159 getNumberOfTrials() - x); 160 } 161 return ret; 162 } 163 164 /** 165 * For this distribution, X, this method returns the largest x, such 166 * that P(X ≤ x) ≤ <code>p</code>. 167 * <p> 168 * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code> for 169 * p=1.</p> 170 * 171 * @param p the desired probability 172 * @return the largest x such that P(X ≤ x) <= p 173 * @throws MathException if the inverse cumulative probability can not be 174 * computed due to convergence or other numerical errors. 175 * @throws IllegalArgumentException if p < 0 or p > 1 176 */ 177 public int inverseCumulativeProbability(final double p) throws MathException { 178 // handle extreme values explicitly 179 if (p == 0) { 180 return -1; 181 } 182 if (p == 1) { 183 return Integer.MAX_VALUE; 184 } 185 186 // use default bisection impl 187 return super.inverseCumulativeProbability(p); 188 } 189 }