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.MathRuntimeException;
23 import org.apache.commons.math.special.Beta;
24 import org.apache.commons.math.util.MathUtils;
25
26 /**
27 * The default implementation of {@link BinomialDistribution}.
28 *
29 * @version $Revision: 772119 $ $Date: 2009-05-06 05:43:28 -0400 (Wed, 06 May 2009) $
30 */
31 public class BinomialDistributionImpl
32 extends AbstractIntegerDistribution
33 implements BinomialDistribution, Serializable {
34
35 /** Serializable version identifier */
36 private static final long serialVersionUID = 6751309484392813623L;
37
38 /** The number of trials. */
39 private int numberOfTrials;
40
41 /** The probability of success. */
42 private double probabilityOfSuccess;
43
44 /**
45 * Create a binomial distribution with the given number of trials and
46 * probability of success.
47 * @param trials the number of trials.
48 * @param p the probability of success.
49 */
50 public BinomialDistributionImpl(int trials, double p) {
51 super();
52 setNumberOfTrials(trials);
53 setProbabilityOfSuccess(p);
54 }
55
56 /**
57 * Access the number of trials for this distribution.
58 * @return the number of trials.
59 */
60 public int getNumberOfTrials() {
61 return numberOfTrials;
62 }
63
64 /**
65 * Access the probability of success for this distribution.
66 * @return the probability of success.
67 */
68 public double getProbabilityOfSuccess() {
69 return probabilityOfSuccess;
70 }
71
72 /**
73 * Change the number of trials for this distribution.
74 * @param trials the new number of trials.
75 * @throws IllegalArgumentException if <code>trials</code> is not a valid
76 * number of trials.
77 */
78 public void setNumberOfTrials(int trials) {
79 if (trials < 0) {
80 throw MathRuntimeException.createIllegalArgumentException(
81 "number of trials must be non-negative ({0})", trials);
82 }
83 numberOfTrials = trials;
84 }
85
86 /**
87 * Change the probability of success for this distribution.
88 * @param p the new probability of success.
89 * @throws IllegalArgumentException if <code>p</code> is not a valid
90 * probability.
91 */
92 public void setProbabilityOfSuccess(double p) {
93 if (p < 0.0 || p > 1.0) {
94 throw MathRuntimeException.createIllegalArgumentException(
95 "{0} out of [{1}, {2}] range", p, 0.0, 1.0);
96 }
97 probabilityOfSuccess = p;
98 }
99
100 /**
101 * Access the domain value lower bound, based on <code>p</code>, used to
102 * bracket a PDF root.
103 *
104 * @param p the desired probability for the critical value
105 * @return domain value lower bound, i.e.
106 * P(X < <i>lower bound</i>) < <code>p</code>
107 */
108 @Override
109 protected int getDomainLowerBound(double p) {
110 return -1;
111 }
112
113 /**
114 * Access the domain value upper bound, based on <code>p</code>, used to
115 * bracket a PDF root.
116 *
117 * @param p the desired probability for the critical value
118 * @return domain value upper bound, i.e.
119 * P(X < <i>upper bound</i>) > <code>p</code>
120 */
121 @Override
122 protected int getDomainUpperBound(double p) {
123 return getNumberOfTrials();
124 }
125
126 /**
127 * For this distribution, X, this method returns P(X ≤ x).
128 * @param x the value at which the PDF is evaluated.
129 * @return PDF for this distribution.
130 * @throws MathException if the cumulative probability can not be
131 * computed due to convergence or other numerical errors.
132 */
133 @Override
134 public double cumulativeProbability(int x) throws MathException {
135 double ret;
136 if (x < 0) {
137 ret = 0.0;
138 } else if (x >= getNumberOfTrials()) {
139 ret = 1.0;
140 } else {
141 ret =
142 1.0 - Beta.regularizedBeta(
143 getProbabilityOfSuccess(),
144 x + 1.0,
145 getNumberOfTrials() - x);
146 }
147 return ret;
148 }
149
150 /**
151 * For this distribution, X, this method returns P(X = x).
152 *
153 * @param x the value at which the PMF is evaluated.
154 * @return PMF for this distribution.
155 */
156 public double probability(int x) {
157 double ret;
158 if (x < 0 || x > getNumberOfTrials()) {
159 ret = 0.0;
160 } else {
161 ret = MathUtils.binomialCoefficientDouble(
162 getNumberOfTrials(), x) *
163 Math.pow(getProbabilityOfSuccess(), x) *
164 Math.pow(1.0 - getProbabilityOfSuccess(),
165 getNumberOfTrials() - x);
166 }
167 return ret;
168 }
169
170 /**
171 * For this distribution, X, this method returns the largest x, such
172 * that P(X ≤ x) ≤ <code>p</code>.
173 * <p>
174 * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code> for
175 * p=1.</p>
176 *
177 * @param p the desired probability
178 * @return the largest x such that P(X ≤ x) <= p
179 * @throws MathException if the inverse cumulative probability can not be
180 * computed due to convergence or other numerical errors.
181 * @throws IllegalArgumentException if p < 0 or p > 1
182 */
183 @Override
184 public int inverseCumulativeProbability(final double p) throws MathException {
185 // handle extreme values explicitly
186 if (p == 0) {
187 return -1;
188 }
189 if (p == 1) {
190 return Integer.MAX_VALUE;
191 }
192
193 // use default bisection impl
194 return super.inverseCumulativeProbability(p);
195 }
196 }