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 PascalDistribution}.
27 * @version $Revision: 617953 $ $Date: 2008-02-02 22:54:00 -0700 (Sat, 02 Feb 2008) $
28 * @since 1.2
29 */
30 public class PascalDistributionImpl extends AbstractIntegerDistribution
31 implements PascalDistribution, Serializable {
32
33 /** Serializable version identifier */
34 private static final long serialVersionUID = 6751309484392813623L;
35
36 /** The number of successes */
37 private int numberOfSuccesses;
38
39 /** The probability of success */
40 private double probabilityOfSuccess;
41
42 /**
43 * Create a binomial distribution with the given number of trials and
44 * probability of success.
45 * @param r the number of successes
46 * @param p the probability of success
47 */
48 public PascalDistributionImpl(int r, double p) {
49 super();
50 setNumberOfSuccesses(r);
51 setProbabilityOfSuccess(p);
52 }
53
54 /**
55 * Access the number of successes for this distribution.
56 * @return the number of successes
57 */
58 public int getNumberOfSuccesses() {
59 return numberOfSuccesses;
60 }
61
62 /**
63 * Access the probability of success for this distribution.
64 * @return the probability of success
65 */
66 public double getProbabilityOfSuccess() {
67 return probabilityOfSuccess;
68 }
69
70 /**
71 * Change the number of successes for this distribution.
72 * @param successes the new number of successes
73 * @throws IllegalArgumentException if <code>successes</code> is not
74 * positive.
75 */
76 public void setNumberOfSuccesses(int successes) {
77 if (successes < 0) {
78 throw new IllegalArgumentException(
79 "number of successes must be non-negative.");
80 }
81 numberOfSuccesses = successes;
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(
93 "probability of success must be between 0.0 and 1.0, inclusive.");
94 }
95 probabilityOfSuccess = p;
96 }
97
98 /**
99 * Access the domain value lower bound, based on <code>p</code>, used to
100 * bracket a PDF root.
101 * @param p the desired probability for the critical value
102 * @return domain value lower bound, i.e. P(X < <i>lower bound</i>) <
103 * <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 * @param p the desired probability for the critical value
113 * @return domain value upper bound, i.e. P(X < <i>upper bound</i>) >
114 * <code>p</code>
115 */
116 protected int getDomainUpperBound(double p) {
117 // use MAX - 1 because MAX causes loop
118 return Integer.MAX_VALUE - 1;
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 computed
126 * 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 {
133 ret = Beta.regularizedBeta(getProbabilityOfSuccess(),
134 getNumberOfSuccesses(), x + 1);
135 }
136 return ret;
137 }
138
139 /**
140 * For this distribution, X, this method returns P(X = x).
141 * @param x the value at which the PMF is evaluated
142 * @return PMF for this distribution
143 */
144 public double probability(int x) {
145 double ret;
146 if (x < 0) {
147 ret = 0.0;
148 } else {
149 ret = MathUtils.binomialCoefficientDouble(x +
150 getNumberOfSuccesses() - 1, getNumberOfSuccesses() - 1) *
151 Math.pow(getProbabilityOfSuccess(), getNumberOfSuccesses()) *
152 Math.pow(1.0 - getProbabilityOfSuccess(), x);
153 }
154 return ret;
155 }
156
157 /**
158 * For this distribution, X, this method returns the largest x, such that
159 * P(X ≤ x) ≤ <code>p</code>.
160 * <p>
161 * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code>
162 * for p=1.</p>
163 * @param p the desired probability
164 * @return the largest x such that P(X ≤ x) <= p
165 * @throws MathException if the inverse cumulative probability can not be
166 * computed due to convergence or other numerical errors.
167 * @throws IllegalArgumentException if p < 0 or p > 1
168 */
169 public int inverseCumulativeProbability(final double p)
170 throws MathException {
171 int ret;
172
173 // handle extreme values explicitly
174 if (p == 0) {
175 ret = -1;
176 } else if (p == 1) {
177 ret = Integer.MAX_VALUE;
178 } else {
179 ret = super.inverseCumulativeProbability(p);
180 }
181
182 return ret;
183 }
184 }