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.math3.distribution; import org.apache.commons.math3.exception.OutOfRangeException; import org.apache.commons.math3.exception.NotPositiveException; import org.apache.commons.math3.exception.util.LocalizedFormats; import org.apache.commons.math3.special.Beta; import org.apache.commons.math3.util.FastMath; import org.apache.commons.math3.random.RandomGenerator; import org.apache.commons.math3.random.Well19937c; /** * Implementation of the binomial distribution. * * @see <a href="http://en.wikipedia.org/wiki/Binomial_distribution">Binomial distribution (Wikipedia)</a> * @see <a href="http://mathworld.wolfram.com/BinomialDistribution.html">Binomial Distribution (MathWorld)</a> * @version $Id: BinomialDistribution.java 1416643 2012-12-03 19:37:14Z tn $ */ public class BinomialDistribution extends AbstractIntegerDistribution { /** Serializable version identifier. */ private static final long serialVersionUID = 6751309484392813623L; /** The number of trials. */ private final int numberOfTrials; /** The probability of success. */ private final double probabilityOfSuccess; /** * Create a binomial distribution with the given number of trials and * probability of success. * * @param trials Number of trials. * @param p Probability of success. * @throws NotPositiveException if {@code trials < 0}. * @throws OutOfRangeException if {@code p < 0} or {@code p > 1}. */ public BinomialDistribution(int trials, double p) { this(new Well19937c(), trials, p); } /** * Creates a binomial distribution. * * @param rng Random number generator. * @param trials Number of trials. * @param p Probability of success. * @throws NotPositiveException if {@code trials < 0}. * @throws OutOfRangeException if {@code p < 0} or {@code p > 1}. * @since 3.1 */ public BinomialDistribution(RandomGenerator rng, int trials, double p) { super(rng); if (trials < 0) { throw new NotPositiveException(LocalizedFormats.NUMBER_OF_TRIALS, trials); } if (p < 0 || p > 1) { throw new OutOfRangeException(p, 0, 1); } probabilityOfSuccess = p; numberOfTrials = trials; } /** * 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; } /** {@inheritDoc} */ 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; } /** {@inheritDoc} */ public double cumulativeProbability(int x) { double ret; if (x < 0) { ret = 0.0; } else if (x >= numberOfTrials) { ret = 1.0; } else { ret = 1.0 - Beta.regularizedBeta(probabilityOfSuccess, x + 1.0, numberOfTrials - x); } return ret; } /** * {@inheritDoc} * * For {@code n} trials and probability parameter {@code p}, the mean is * {@code n * p}. */ public double getNumericalMean() { return numberOfTrials * probabilityOfSuccess; } /** * {@inheritDoc} * * For {@code n} trials and probability parameter {@code p}, the variance is * {@code n * p * (1 - p)}. */ public double getNumericalVariance() { final double p = probabilityOfSuccess; return numberOfTrials * p * (1 - p); } /** * {@inheritDoc} * * The lower bound of the support is always 0 except for the probability * parameter {@code p = 1}. * * @return lower bound of the support (0 or the number of trials) */ public int getSupportLowerBound() { return probabilityOfSuccess < 1.0 ? 0 : numberOfTrials; } /** * {@inheritDoc} * * The upper bound of the support is the number of trials except for the * probability parameter {@code p = 0}. * * @return upper bound of the support (number of trials or 0) */ public int getSupportUpperBound() { return probabilityOfSuccess > 0.0 ? numberOfTrials : 0; } /** * {@inheritDoc} * * The support of this distribution is connected. * * @return {@code true} */ public boolean isSupportConnected() { return true; } }