/* * 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: *
* 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);
}
}