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 package org.apache.commons.math.distribution; 018 019 import java.io.Serializable; 020 021 import org.apache.commons.math.MathException; 022 import org.apache.commons.math.MathRuntimeException; 023 import org.apache.commons.math.special.Beta; 024 import org.apache.commons.math.util.MathUtils; 025 026 /** 027 * The default implementation of {@link PascalDistribution}. 028 * @version $Revision: 920852 $ $Date: 2010-03-09 07:53:44 -0500 (Tue, 09 Mar 2010) $ 029 * @since 1.2 030 */ 031 public class PascalDistributionImpl extends AbstractIntegerDistribution 032 implements PascalDistribution, Serializable { 033 034 /** Serializable version identifier */ 035 private static final long serialVersionUID = 6751309484392813623L; 036 037 /** The number of successes */ 038 private int numberOfSuccesses; 039 040 /** The probability of success */ 041 private double probabilityOfSuccess; 042 043 /** 044 * Create a binomial distribution with the given number of trials and 045 * probability of success. 046 * @param r the number of successes 047 * @param p the probability of success 048 */ 049 public PascalDistributionImpl(int r, double p) { 050 super(); 051 setNumberOfSuccessesInternal(r); 052 setProbabilityOfSuccessInternal(p); 053 } 054 055 /** 056 * Access the number of successes for this distribution. 057 * @return the number of successes 058 */ 059 public int getNumberOfSuccesses() { 060 return numberOfSuccesses; 061 } 062 063 /** 064 * Access the probability of success for this distribution. 065 * @return the probability of success 066 */ 067 public double getProbabilityOfSuccess() { 068 return probabilityOfSuccess; 069 } 070 071 /** 072 * Change the number of successes for this distribution. 073 * @param successes the new number of successes 074 * @throws IllegalArgumentException if <code>successes</code> is not 075 * positive. 076 * @deprecated as of 2.1 (class will become immutable in 3.0) 077 */ 078 @Deprecated 079 public void setNumberOfSuccesses(int successes) { 080 setNumberOfSuccessesInternal(successes); 081 } 082 /** 083 * Change the number of successes for this distribution. 084 * @param successes the new number of successes 085 * @throws IllegalArgumentException if <code>successes</code> is not 086 * positive. 087 */ 088 private void setNumberOfSuccessesInternal(int successes) { 089 if (successes < 0) { 090 throw MathRuntimeException.createIllegalArgumentException( 091 "number of successes must be non-negative ({0})", 092 successes); 093 } 094 numberOfSuccesses = successes; 095 } 096 097 /** 098 * Change the probability of success for this distribution. 099 * @param p the new probability of success 100 * @throws IllegalArgumentException if <code>p</code> is not a valid 101 * probability. 102 * @deprecated as of 2.1 (class will become immutable in 3.0) 103 */ 104 @Deprecated 105 public void setProbabilityOfSuccess(double p) { 106 setProbabilityOfSuccessInternal(p); 107 } 108 /** 109 * Change the probability of success for this distribution. 110 * @param p the new probability of success 111 * @throws IllegalArgumentException if <code>p</code> is not a valid 112 * probability. 113 */ 114 private void setProbabilityOfSuccessInternal(double p) { 115 if (p < 0.0 || p > 1.0) { 116 throw MathRuntimeException.createIllegalArgumentException( 117 "{0} out of [{1}, {2}] range", p, 0.0, 1.0); 118 } 119 probabilityOfSuccess = p; 120 } 121 122 /** 123 * Access the domain value lower bound, based on <code>p</code>, used to 124 * bracket a PDF root. 125 * @param p the desired probability for the critical value 126 * @return domain value lower bound, i.e. P(X < <i>lower bound</i>) < 127 * <code>p</code> 128 */ 129 @Override 130 protected int getDomainLowerBound(double p) { 131 return -1; 132 } 133 134 /** 135 * Access the domain value upper bound, based on <code>p</code>, used to 136 * bracket a PDF root. 137 * @param p the desired probability for the critical value 138 * @return domain value upper bound, i.e. P(X < <i>upper bound</i>) > 139 * <code>p</code> 140 */ 141 @Override 142 protected int getDomainUpperBound(double p) { 143 // use MAX - 1 because MAX causes loop 144 return Integer.MAX_VALUE - 1; 145 } 146 147 /** 148 * For this distribution, X, this method returns P(X ≤ x). 149 * @param x the value at which the PDF is evaluated 150 * @return PDF for this distribution 151 * @throws MathException if the cumulative probability can not be computed 152 * due to convergence or other numerical errors 153 */ 154 @Override 155 public double cumulativeProbability(int x) throws MathException { 156 double ret; 157 if (x < 0) { 158 ret = 0.0; 159 } else { 160 ret = Beta.regularizedBeta(probabilityOfSuccess, 161 numberOfSuccesses, x + 1); 162 } 163 return ret; 164 } 165 166 /** 167 * For this distribution, X, this method returns P(X = x). 168 * @param x the value at which the PMF is evaluated 169 * @return PMF for this distribution 170 */ 171 public double probability(int x) { 172 double ret; 173 if (x < 0) { 174 ret = 0.0; 175 } else { 176 ret = MathUtils.binomialCoefficientDouble(x + 177 numberOfSuccesses - 1, numberOfSuccesses - 1) * 178 Math.pow(probabilityOfSuccess, numberOfSuccesses) * 179 Math.pow(1.0 - probabilityOfSuccess, x); 180 } 181 return ret; 182 } 183 184 /** 185 * For this distribution, X, this method returns the largest x, such that 186 * P(X ≤ x) ≤ <code>p</code>. 187 * <p> 188 * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code> 189 * for p=1.</p> 190 * @param p the desired probability 191 * @return the largest x such that P(X ≤ x) <= p 192 * @throws MathException if the inverse cumulative probability can not be 193 * computed due to convergence or other numerical errors. 194 * @throws IllegalArgumentException if p < 0 or p > 1 195 */ 196 @Override 197 public int inverseCumulativeProbability(final double p) 198 throws MathException { 199 int ret; 200 201 // handle extreme values explicitly 202 if (p == 0) { 203 ret = -1; 204 } else if (p == 1) { 205 ret = Integer.MAX_VALUE; 206 } else { 207 ret = super.inverseCumulativeProbability(p); 208 } 209 210 return ret; 211 } 212 }