Java tutorial
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.commons.math.distribution; import java.io.Serializable; import org.apache.commons.math.MathException; import org.apache.commons.math.MathRuntimeException; import org.apache.commons.math.exception.util.LocalizedFormats; import org.apache.commons.math.special.Beta; import org.apache.commons.math.util.FastMath; /** * The default implementation of {@link BinomialDistribution}. * * @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $ */ public class BinomialDistributionImpl extends AbstractIntegerDistribution implements BinomialDistribution, Serializable { /** Serializable version identifier */ private static final long serialVersionUID = 6751309484392813623L; /** The number of trials. */ private int numberOfTrials; /** The probability of success. */ private double probabilityOfSuccess; /** * Create a binomial distribution with the given number of trials and * probability of success. * * @param trials the number of trials. * @param p the probability of success. */ public BinomialDistributionImpl(int trials, double p) { super(); setNumberOfTrialsInternal(trials); setProbabilityOfSuccessInternal(p); } /** * Access the number of trials for this distribution. * * @return the number of trials. */ public int getNumberOfTrials() { return numberOfTrials; } /** * Access the probability of success for this distribution. * * @return the probability of success. */ public double getProbabilityOfSuccess() { return probabilityOfSuccess; } /** * Change the number of trials for this distribution. * * @param trials the new number of trials. * @throws IllegalArgumentException if <code>trials</code> is not a valid * number of trials. * @deprecated as of 2.1 (class will become immutable in 3.0) */ @Deprecated public void setNumberOfTrials(int trials) { setNumberOfTrialsInternal(trials); } /** * Change the number of trials for this distribution. * * @param trials the new number of trials. * @throws IllegalArgumentException if <code>trials</code> is not a valid * number of trials. */ private void setNumberOfTrialsInternal(int trials) { if (trials < 0) { throw MathRuntimeException.createIllegalArgumentException(LocalizedFormats.NEGATIVE_NUMBER_OF_TRIALS, trials); } numberOfTrials = trials; } /** * Change the probability of success for this distribution. * * @param p the new probability of success. * @throws IllegalArgumentException if <code>p</code> is not a valid * probability. * @deprecated as of 2.1 (class will become immutable in 3.0) */ @Deprecated public void setProbabilityOfSuccess(double p) { setProbabilityOfSuccessInternal(p); } /** * Change the probability of success for this distribution. * * @param p the new probability of success. * @throws IllegalArgumentException if <code>p</code> is not a valid * probability. */ private void setProbabilityOfSuccessInternal(double p) { if (p < 0.0 || p > 1.0) { throw MathRuntimeException.createIllegalArgumentException(LocalizedFormats.OUT_OF_RANGE_SIMPLE, p, 0.0, 1.0); } probabilityOfSuccess = p; } /** * Access the domain value lower bound, based on <code>p</code>, used to * bracket a PDF root. * * @param p the desired probability for the critical value * @return domain value lower bound, i.e. P(X < <i>lower bound</i>) < * <code>p</code> */ @Override protected int getDomainLowerBound(double p) { return -1; } /** * Access the domain value upper bound, based on <code>p</code>, used to * bracket a PDF root. * * @param p the desired probability for the critical value * @return domain value upper bound, i.e. P(X < <i>upper bound</i>) > * <code>p</code> */ @Override protected int getDomainUpperBound(double p) { return numberOfTrials; } /** * For this distribution, X, this method returns P(X ≤ x). * * @param x the value at which the PDF is evaluated. * @return PDF for this distribution. * @throws MathException if the cumulative probability can not be computed * due to convergence or other numerical errors. */ @Override public double cumulativeProbability(int x) throws MathException { double ret; if (x < 0) { ret = 0.0; } else if (x >= numberOfTrials) { ret = 1.0; } else { ret = 1.0 - Beta.regularizedBeta(getProbabilityOfSuccess(), x + 1.0, numberOfTrials - x); } return ret; } /** * For this distribution, X, this method returns P(X = x). * * @param x the value at which the PMF is evaluated. * @return PMF for this distribution. */ public double probability(int x) { double ret; if (x < 0 || x > numberOfTrials) { ret = 0.0; } else { ret = FastMath.exp(SaddlePointExpansion.logBinomialProbability(x, numberOfTrials, probabilityOfSuccess, 1.0 - probabilityOfSuccess)); } return ret; } /** * For this distribution, X, this method returns the largest x, such that * P(X ≤ x) ≤ <code>p</code>. * <p> * Returns <code>-1</code> for p=0 and <code>Integer.MAX_VALUE</code> for * p=1. * </p> * * @param p the desired probability * @return the largest x such that P(X ≤ x) <= p * @throws MathException if the inverse cumulative probability can not be * computed due to convergence or other numerical errors. * @throws IllegalArgumentException if p < 0 or p > 1 */ @Override public int inverseCumulativeProbability(final double p) throws MathException { // handle extreme values explicitly if (p == 0) { return -1; } if (p == 1) { return Integer.MAX_VALUE; } // use default bisection impl return super.inverseCumulativeProbability(p); } /** * Returns the lower bound of the support for the distribution. * * The lower bound of the support is always 0 no matter the number of trials * and probability parameter. * * @return lower bound of the support (always 0) * @since 2.2 */ public int getSupportLowerBound() { return 0; } /** * Returns the upper bound of the support for the distribution. * * The upper bound of the support is the number of trials. * * @return upper bound of the support (equal to number of trials) * @since 2.2 */ public int getSupportUpperBound() { return getNumberOfTrials(); } /** * Returns the mean. * * For <code>n</code> number of trials and * probability parameter <code>p</code>, the mean is * <code>n * p</code> * * @return the mean * @since 2.2 */ public double getNumericalMean() { return (double) getNumberOfTrials() * getProbabilityOfSuccess(); } /** * Returns the variance. * * For <code>n</code> number of trials and * probability parameter <code>p</code>, the variance is * <code>n * p * (1 - p)</code> * * @return the variance * @since 2.2 */ public double getNumericalVariance() { final double p = getProbabilityOfSuccess(); return (double) getNumberOfTrials() * p * (1 - p); } }