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Java > Open Source Codes > org > apache > commons > math > distribution > DistributionFactoryImpl


1 /*
2  * Copyright 2003-2004 The Apache Software Foundation.
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 package org.apache.commons.math.distribution;
17
18 /**
19  * A concrete distribution factory. This is the default factory used by
20  * Commons-Math.
21  *
22  * @version $Revision$ $Date: 2005-06-26 15:20:57 -0700 (Sun, 26 Jun 2005) $
23  */
24 public class DistributionFactoryImpl extends DistributionFactory {
25
26     /**
27      * Default constructor. Package scope to prevent unwanted instantiation.
28      */
29     public DistributionFactoryImpl() {
30         super();
31     }
32     
33     /**
34      * Create a new chi-square distribution with the given degrees of freedom.
35      *
36      * @param degreesOfFreedom degrees of freedom
37      * @return a new chi-square distribution
38      */
39     public ChiSquaredDistribution createChiSquareDistribution(
40         final double degreesOfFreedom) {
41             
42         return new ChiSquaredDistributionImpl(degreesOfFreedom);
43     }
44     
45     /**
46      * Create a new gamma distribution the given shape and scale parameters.
47      *
48      * @param alpha the shape parameter
49      * @param beta the scale parameter
50      * @return a new gamma distribution
51      */
52     public GammaDistribution createGammaDistribution(
53         double alpha, double beta) {
54
55         return new GammaDistributionImpl(alpha, beta);
56     }
57
58     /**
59      * Create a new t distribution with the given degrees of freedom.
60      *
61      * @param degreesOfFreedom degrees of freedom
62      * @return a new t distribution.
63      */
64     public TDistribution createTDistribution(double degreesOfFreedom) {
65         return new TDistributionImpl(degreesOfFreedom);
66     }
67
68     /**
69      * Create a new F-distribution with the given degrees of freedom.
70      *
71      * @param numeratorDegreesOfFreedom numerator degrees of freedom
72      * @param denominatorDegreesOfFreedom denominator degrees of freedom
73      * @return a new F-distribution
74      */
75     public FDistribution createFDistribution(
76         double numeratorDegreesOfFreedom,
77         double denominatorDegreesOfFreedom) {
78         return new FDistributionImpl(numeratorDegreesOfFreedom,
79             denominatorDegreesOfFreedom);
80     }
81
82     /**
83      * Create a new exponential distribution with the given degrees of freedom.
84      *
85      * @param mean mean
86      * @return a new exponential distribution
87      */
88     public ExponentialDistribution createExponentialDistribution(double mean) {
89         return new ExponentialDistributionImpl(mean);
90     }
91
92     /**
93      * Create a binomial distribution with the given number of trials and
94      * probability of success.
95      *
96      * @param numberOfTrials the number of trials
97      * @param probabilityOfSuccess the probability of success
98      * @return a new binomial distribution
99      */
100     public BinomialDistribution createBinomialDistribution(
101         int numberOfTrials, double probabilityOfSuccess) {
102         return new BinomialDistributionImpl(numberOfTrials,
103             probabilityOfSuccess);
104     }
105
106     /**
107      * Create a new hypergeometric distribution with the given the population
108      * size, the number of successes in the population, and the sample size.
109      *
110      * @param populationSize the population size
111      * @param numberOfSuccesses number of successes in the population
112      * @param sampleSize the sample size
113      * @return a new hypergeometric desitribution
114      */
115     public HypergeometricDistribution createHypergeometricDistribution(
116         int populationSize, int numberOfSuccesses, int sampleSize) {
117         return new HypergeometricDistributionImpl(populationSize,
118             numberOfSuccesses, sampleSize);
119     }
120
121     /**
122      * Create a new normal distribution with the given mean and standard
123      * deviation.
124      *
125      * @param mean the mean of the distribution
126      * @param sd standard deviation
127      * @return a new normal distribution
128      */
129     public NormalDistribution createNormalDistribution(double mean, double sd) {
130         return new NormalDistributionImpl(mean, sd);
131     }
132
133     /**
134      * Create a new normal distribution with the mean zero and standard
135      * deviation one.
136      *
137      * @return a new normal distribution
138      */
139     public NormalDistribution createNormalDistribution() {
140         return new NormalDistributionImpl();
141     }
142     
143     /**
144      * Create a new Poisson distribution with poisson parameter lambda.
145      * <p>
146      * lambda must be postive; otherwise an
147      * <code>IllegalArgumentException</code> is thrown.
148      *
149      * @param lambda poisson parameter
150      * @return a new Poisson distribution
151      * @throws IllegalArgumentException if lambda &le; 0
152      */
153     public PoissonDistribution createPoissonDistribution(double lambda) {
154         return new PoissonDistributionImpl(lambda);
155     }
156
157 }
158
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