/* * 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; /** * A concrete distribution factory. This is the default factory used by * Commons-Math. * * @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 class DistributionFactoryImpl extends DistributionFactory { /** * Default constructor. Package scope to prevent unwanted instantiation. */ public DistributionFactoryImpl() { super(); } /** * Create a new chi-square distribution with the given degrees of freedom. * * @param degreesOfFreedom degrees of freedom * @return a new chi-square distribution */ public ChiSquaredDistribution createChiSquareDistribution( final double degreesOfFreedom) { return new ChiSquaredDistributionImpl(degreesOfFreedom); } /** * Create a new gamma distribution the given shape and scale parameters. * * @param alpha the shape parameter * @param beta the scale parameter * @return a new gamma distribution */ public GammaDistribution createGammaDistribution( double alpha, double beta) { return new GammaDistributionImpl(alpha, beta); } /** * Create a new t distribution with the given degrees of freedom. * * @param degreesOfFreedom degrees of freedom * @return a new t distribution. */ public TDistribution createTDistribution(double degreesOfFreedom) { return new TDistributionImpl(degreesOfFreedom); } /** * 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 FDistribution createFDistribution( double numeratorDegreesOfFreedom, double denominatorDegreesOfFreedom) { return new FDistributionImpl(numeratorDegreesOfFreedom, denominatorDegreesOfFreedom); } /** * Create a new exponential distribution with the given degrees of freedom. * * @param mean mean * @return a new exponential distribution */ public ExponentialDistribution createExponentialDistribution(double mean) { return new ExponentialDistributionImpl(mean); } /** * 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 BinomialDistribution createBinomialDistribution( int numberOfTrials, double probabilityOfSuccess) { return new BinomialDistributionImpl(numberOfTrials, probabilityOfSuccess); } /** * 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 HypergeometricDistribution createHypergeometricDistribution( int populationSize, int numberOfSuccesses, int sampleSize) { return new HypergeometricDistributionImpl(populationSize, numberOfSuccesses, 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 NormalDistribution createNormalDistribution(double mean, double sd) { return new NormalDistributionImpl(mean, sd); } /** * Create a new normal distribution with the mean zero and standard * deviation one. * * @return a new normal distribution */ public NormalDistribution createNormalDistribution() { return new NormalDistributionImpl(); } /** * Create a new Poisson distribution with poisson parameter lambda. *

* lambda must be postive; otherwise an * IllegalArgumentException is thrown. * * @param lambda poisson parameter * @return a new Poisson distribution * @throws IllegalArgumentException if lambda ≤ 0 */ public PoissonDistribution createPoissonDistribution(double lambda) { return new PoissonDistributionImpl(lambda); } }