/*
* Copyright 2003-2004 The Apache Software Foundation.
*
* Licensed 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 org.apache.commons.discovery.tools.DiscoverClass;
/**
* This factory provids the means to create common statistical distributions.
* The following distributions are supported:
* <ul>
* <li>Binomial</li>
* <li>Chi-Squared</li>
* <li>Exponential</li>
* <li>F</li>
* <li>Gamma</li>
* <li>HyperGeometric</li>
* <li>Poisson</li>
* <li>Normal</li>
* <li>Student's t</li>
* </ul>
*
* Common usage:<pre>
* DistributionFactory factory = DistributionFactory.newInstance();
*
* // create a Chi-Square distribution with 5 degrees of freedom.
* ChiSquaredDistribution chi = factory.createChiSquareDistribution(5.0);
* </pre>
*
* @version $Revision: 1.22 $ $Date: 2004/11/07 03:32:48 $
*/
public abstract class DistributionFactory {
/**
* Default constructor.
*/
protected DistributionFactory() {
super();
}
/**
* Create an instance of a <code>DistributionFactory</code>
* @return a new factory.
*/
public static DistributionFactory newInstance() {
DistributionFactory factory = null;
try {
DiscoverClass dc = new DiscoverClass();
factory = (DistributionFactory) dc.newInstance(
DistributionFactory.class,
"org.apache.commons.math.distribution.DistributionFactoryImpl");
} catch(Throwable t) {
return new DistributionFactoryImpl();
}
return factory;
}
/**
* 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 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 normal distribution.
*/
public abstract PoissonDistribution
createPoissonDistribution(double lambda);
}