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    
025    /**
026     * The default implementation of {@link BinomialDistribution}.
027     *
028     * @version $Revision: 920852 $ $Date: 2010-03-09 07:53:44 -0500 (Tue, 09 Mar 2010) $
029     */
030    public class BinomialDistributionImpl extends AbstractIntegerDistribution
031            implements BinomialDistribution, Serializable {
032    
033        /** Serializable version identifier */
034        private static final long serialVersionUID = 6751309484392813623L;
035    
036        /** The number of trials. */
037        private int numberOfTrials;
038    
039        /** The probability of success. */
040        private double probabilityOfSuccess;
041    
042        /**
043         * Create a binomial distribution with the given number of trials and
044         * probability of success.
045         *
046         * @param trials the number of trials.
047         * @param p the probability of success.
048         */
049        public BinomialDistributionImpl(int trials, double p) {
050            super();
051            setNumberOfTrialsInternal(trials);
052            setProbabilityOfSuccessInternal(p);
053        }
054    
055        /**
056         * Access the number of trials for this distribution.
057         *
058         * @return the number of trials.
059         */
060        public int getNumberOfTrials() {
061            return numberOfTrials;
062        }
063    
064        /**
065         * Access the probability of success for this distribution.
066         *
067         * @return the probability of success.
068         */
069        public double getProbabilityOfSuccess() {
070            return probabilityOfSuccess;
071        }
072    
073        /**
074         * Change the number of trials for this distribution.
075         *
076         * @param trials the new number of trials.
077         * @throws IllegalArgumentException if <code>trials</code> is not a valid
078         *             number of trials.
079         * @deprecated as of 2.1 (class will become immutable in 3.0)
080         */
081        @Deprecated
082        public void setNumberOfTrials(int trials) {
083            setNumberOfTrialsInternal(trials);
084        }
085        /**
086         * Change the number of trials for this distribution.
087         *
088         * @param trials the new number of trials.
089         * @throws IllegalArgumentException if <code>trials</code> is not a valid
090         *             number of trials.
091         */
092        private void setNumberOfTrialsInternal(int trials) {
093            if (trials < 0) {
094                throw MathRuntimeException.createIllegalArgumentException(
095                        "number of trials must be non-negative ({0})", trials);
096            }
097            numberOfTrials = trials;
098        }
099    
100        /**
101         * Change the probability of success for this distribution.
102         *
103         * @param p the new probability of success.
104         * @throws IllegalArgumentException if <code>p</code> is not a valid
105         *             probability.
106         * @deprecated as of 2.1 (class will become immutable in 3.0)
107         */
108        @Deprecated
109        public void setProbabilityOfSuccess(double p) {
110            setProbabilityOfSuccessInternal(p);
111        }
112        /**
113         * Change the probability of success for this distribution.
114         *
115         * @param p the new probability of success.
116         * @throws IllegalArgumentException if <code>p</code> is not a valid
117         *             probability.
118         */
119        private void setProbabilityOfSuccessInternal(double p) {
120            if (p < 0.0 || p > 1.0) {
121                throw MathRuntimeException.createIllegalArgumentException(
122                        "{0} out of [{1}, {2}] range", p, 0.0, 1.0);
123            }
124            probabilityOfSuccess = p;
125        }
126    
127        /**
128         * Access the domain value lower bound, based on <code>p</code>, used to
129         * bracket a PDF root.
130         *
131         * @param p the desired probability for the critical value
132         * @return domain value lower bound, i.e. P(X &lt; <i>lower bound</i>) &lt;
133         *         <code>p</code>
134         */
135        @Override
136        protected int getDomainLowerBound(double p) {
137            return -1;
138        }
139    
140        /**
141         * Access the domain value upper bound, based on <code>p</code>, used to
142         * bracket a PDF root.
143         *
144         * @param p the desired probability for the critical value
145         * @return domain value upper bound, i.e. P(X &lt; <i>upper bound</i>) &gt;
146         *         <code>p</code>
147         */
148        @Override
149        protected int getDomainUpperBound(double p) {
150            return numberOfTrials;
151        }
152    
153        /**
154         * For this distribution, X, this method returns P(X &le; x).
155         *
156         * @param x the value at which the PDF is evaluated.
157         * @return PDF for this distribution.
158         * @throws MathException if the cumulative probability can not be computed
159         *             due to convergence or other numerical errors.
160         */
161        @Override
162        public double cumulativeProbability(int x) throws MathException {
163            double ret;
164            if (x < 0) {
165                ret = 0.0;
166            } else if (x >= numberOfTrials) {
167                ret = 1.0;
168            } else {
169                ret = 1.0 - Beta.regularizedBeta(getProbabilityOfSuccess(),
170                        x + 1.0, numberOfTrials - x);
171            }
172            return ret;
173        }
174    
175        /**
176         * For this distribution, X, this method returns P(X = x).
177         *
178         * @param x the value at which the PMF is evaluated.
179         * @return PMF for this distribution.
180         */
181        public double probability(int x) {
182            double ret;
183            if (x < 0 || x > numberOfTrials) {
184                ret = 0.0;
185            } else {
186                ret = Math.exp(SaddlePointExpansion.logBinomialProbability(x,
187                        numberOfTrials, probabilityOfSuccess,
188                        1.0 - probabilityOfSuccess));
189            }
190            return ret;
191        }
192    
193        /**
194         * For this distribution, X, this method returns the largest x, such that
195         * P(X &le; x) &le; <code>p</code>.
196         * <p>
197         * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code> for
198         * p=1.
199         * </p>
200         *
201         * @param p the desired probability
202         * @return the largest x such that P(X &le; x) <= p
203         * @throws MathException if the inverse cumulative probability can not be
204         *             computed due to convergence or other numerical errors.
205         * @throws IllegalArgumentException if p < 0 or p > 1
206         */
207        @Override
208        public int inverseCumulativeProbability(final double p)
209                throws MathException {
210            // handle extreme values explicitly
211            if (p == 0) {
212                return -1;
213            }
214            if (p == 1) {
215                return Integer.MAX_VALUE;
216            }
217    
218            // use default bisection impl
219            return super.inverseCumulativeProbability(p);
220        }
221    }