/* * 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; /** * This factory provids the means to create common statistical distributions. * The following distributions are supported: * * * Common usage:
 * DistributionFactory factory = DistributionFactory.newInstance();
 *
 * // create a Chi-Square distribution with 5 degrees of freedom.
 * ChiSquaredDistribution chi = factory.createChiSquareDistribution(5.0);
 * 
* * @version $Revision: 545192 $ $Date: 2007-06-07 07:35:04 -0700 (Thu, 07 Jun 2007) $ * @deprecated pluggability of distribution instances is now provided through * constructors and setters. */ public abstract class DistributionFactory { /** * Default constructor. */ protected DistributionFactory() { super(); } /** * Create an instance of a DistributionFactory * @return a new factory. */ public static DistributionFactory newInstance() { return new DistributionFactoryImpl(); } /** * Create a binomial distribution with the given number of trials and * probability of success. * * @param numberOfTrials the number of trials. * @param probabilityOfSuccess the probability of success * @return a new binomial distribution */ public abstract BinomialDistribution createBinomialDistribution( int numberOfTrials, double probabilityOfSuccess); /** * Create a Pascal distribution with the given number of successes and * probability of success. * * @param numberOfSuccesses the number of successes. * @param probabilityOfSuccess the probability of success * @return a new Pascal distribution * @since 1.2 */ public PascalDistribution createPascalDistribution( int numberOfSuccesses, double probabilityOfSuccess) { return new PascalDistributionImpl(numberOfSuccesses, probabilityOfSuccess); } /** * Create a new cauchy distribution with the given median and scale. * @param median the median of the distribution * @param scale the scale * @return a new cauchy distribution * @since 1.1 */ public CauchyDistribution createCauchyDistribution( double median, double scale) { return new CauchyDistributionImpl(median, scale); } /** * Create a new chi-square distribution with the given degrees of freedom. * * @param degreesOfFreedom degrees of freedom * @return a new chi-square distribution */ public abstract ChiSquaredDistribution createChiSquareDistribution( double degreesOfFreedom); /** * Create a new exponential distribution with the given degrees of freedom. * * @param mean mean * @return a new exponential distribution */ public abstract ExponentialDistribution createExponentialDistribution( double mean); /** * Create a new F-distribution with the given degrees of freedom. * * @param numeratorDegreesOfFreedom numerator degrees of freedom * @param denominatorDegreesOfFreedom denominator degrees of freedom * @return a new F-distribution */ public abstract FDistribution createFDistribution( double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom); /** * Create a new gamma distribution with the given shape and scale * parameters. * * @param alpha the shape parameter * @param beta the scale parameter * * @return a new gamma distribution */ public abstract GammaDistribution createGammaDistribution( double alpha, double beta); /** * Create a new t distribution with the given degrees of freedom. * * @param degreesOfFreedom degrees of freedom * @return a new t distribution */ public abstract TDistribution createTDistribution(double degreesOfFreedom); /** * Create a new hypergeometric distribution with the given the population * size, the number of successes in the population, and the sample size. * * @param populationSize the population size * @param numberOfSuccesses number of successes in the population * @param sampleSize the sample size * @return a new hypergeometric desitribution */ public abstract HypergeometricDistribution createHypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize); /** * Create a new normal distribution with the given mean and standard * deviation. * * @param mean the mean of the distribution * @param sd standard deviation * @return a new normal distribution */ public abstract NormalDistribution createNormalDistribution(double mean, double sd); /** * Create a new normal distribution with mean zero and standard * deviation one. * * @return a new normal distribution. */ public abstract NormalDistribution createNormalDistribution(); /** * Create a new Poisson distribution with poisson parameter lambda. * * @param lambda poisson parameter * @return a new poisson distribution. */ public abstract PoissonDistribution createPoissonDistribution(double lambda); /** * Create a new Weibull distribution with the given shape and scale * parameters. * * @param alpha the shape parameter. * @param beta the scale parameter. * @return a new Weibull distribution. * @since 1.1 */ public WeibullDistribution createWeibullDistribution( double alpha, double beta) { return new WeibullDistributionImpl(alpha, beta); } }