Classes in this File | Line Coverage | Branch Coverage | Complexity | |||||||
DistributionFactoryImpl |
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| 1.0;1 |
1 | /* |
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2 | * Copyright 2003-2004 The Apache Software Foundation. |
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3 | * |
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4 | * Licensed under the Apache License, Version 2.0 (the "License"); |
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5 | * you may not use this file except in compliance with the License. |
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6 | * You may obtain a copy of the License at |
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7 | * |
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8 | * http://www.apache.org/licenses/LICENSE-2.0 |
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9 | * |
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10 | * Unless required by applicable law or agreed to in writing, software |
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11 | * distributed under the License is distributed on an "AS IS" BASIS, |
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12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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13 | * See the License for the specific language governing permissions and |
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14 | * limitations under the License. |
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15 | */ |
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16 | package org.apache.commons.math.distribution; |
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17 | ||
18 | /** |
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19 | * A concrete distribution factory. This is the default factory used by |
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20 | * Commons-Math. |
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21 | * |
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22 | * @version $Revision$ $Date: 2005-06-26 15:20:57 -0700 (Sun, 26 Jun 2005) $ |
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23 | */ |
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24 | public class DistributionFactoryImpl extends DistributionFactory { |
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25 | ||
26 | /** |
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27 | * Default constructor. Package scope to prevent unwanted instantiation. |
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28 | */ |
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29 | public DistributionFactoryImpl() { |
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30 | 464 | super(); |
31 | 464 | } |
32 | ||
33 | /** |
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34 | * Create a new chi-square distribution with the given degrees of freedom. |
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35 | * |
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36 | * @param degreesOfFreedom degrees of freedom |
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37 | * @return a new chi-square distribution |
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38 | */ |
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39 | public ChiSquaredDistribution createChiSquareDistribution( |
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40 | final double degreesOfFreedom) { |
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41 | ||
42 | 98 | return new ChiSquaredDistributionImpl(degreesOfFreedom); |
43 | } |
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44 | ||
45 | /** |
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46 | * Create a new gamma distribution the given shape and scale parameters. |
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47 | * |
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48 | * @param alpha the shape parameter |
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49 | * @param beta the scale parameter |
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50 | * @return a new gamma distribution |
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51 | */ |
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52 | public GammaDistribution createGammaDistribution( |
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53 | double alpha, double beta) { |
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54 | ||
55 | 142 | return new GammaDistributionImpl(alpha, beta); |
56 | } |
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57 | ||
58 | /** |
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59 | * Create a new t distribution with the given degrees of freedom. |
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60 | * |
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61 | * @param degreesOfFreedom degrees of freedom |
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62 | * @return a new t distribution. |
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63 | */ |
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64 | public TDistribution createTDistribution(double degreesOfFreedom) { |
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65 | 176 | return new TDistributionImpl(degreesOfFreedom); |
66 | } |
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67 | ||
68 | /** |
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69 | * Create a new F-distribution with the given degrees of freedom. |
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70 | * |
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71 | * @param numeratorDegreesOfFreedom numerator degrees of freedom |
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72 | * @param denominatorDegreesOfFreedom denominator degrees of freedom |
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73 | * @return a new F-distribution |
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74 | */ |
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75 | public FDistribution createFDistribution( |
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76 | double numeratorDegreesOfFreedom, |
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77 | double denominatorDegreesOfFreedom) { |
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78 | 26 | return new FDistributionImpl(numeratorDegreesOfFreedom, |
79 | denominatorDegreesOfFreedom); |
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80 | } |
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81 | ||
82 | /** |
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83 | * Create a new exponential distribution with the given degrees of freedom. |
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84 | * |
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85 | * @param mean mean |
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86 | * @return a new exponential distribution |
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87 | */ |
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88 | public ExponentialDistribution createExponentialDistribution(double mean) { |
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89 | 22 | return new ExponentialDistributionImpl(mean); |
90 | } |
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91 | ||
92 | /** |
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93 | * Create a binomial distribution with the given number of trials and |
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94 | * probability of success. |
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95 | * |
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96 | * @param numberOfTrials the number of trials |
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97 | * @param probabilityOfSuccess the probability of success |
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98 | * @return a new binomial distribution |
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99 | */ |
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100 | public BinomialDistribution createBinomialDistribution( |
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101 | int numberOfTrials, double probabilityOfSuccess) { |
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102 | 30 | return new BinomialDistributionImpl(numberOfTrials, |
103 | probabilityOfSuccess); |
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104 | } |
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105 | ||
106 | /** |
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107 | * Create a new hypergeometric distribution with the given the population |
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108 | * size, the number of successes in the population, and the sample size. |
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109 | * |
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110 | * @param populationSize the population size |
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111 | * @param numberOfSuccesses number of successes in the population |
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112 | * @param sampleSize the sample size |
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113 | * @return a new hypergeometric desitribution |
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114 | */ |
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115 | public HypergeometricDistribution createHypergeometricDistribution( |
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116 | int populationSize, int numberOfSuccesses, int sampleSize) { |
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117 | 42 | return new HypergeometricDistributionImpl(populationSize, |
118 | numberOfSuccesses, sampleSize); |
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119 | } |
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120 | ||
121 | /** |
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122 | * Create a new normal distribution with the given mean and standard |
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123 | * deviation. |
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124 | * |
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125 | * @param mean the mean of the distribution |
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126 | * @param sd standard deviation |
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127 | * @return a new normal distribution |
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128 | */ |
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129 | public NormalDistribution createNormalDistribution(double mean, double sd) { |
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130 | 32 | return new NormalDistributionImpl(mean, sd); |
131 | } |
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132 | ||
133 | /** |
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134 | * Create a new normal distribution with the mean zero and standard |
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135 | * deviation one. |
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136 | * |
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137 | * @return a new normal distribution |
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138 | */ |
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139 | public NormalDistribution createNormalDistribution() { |
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140 | 0 | return new NormalDistributionImpl(); |
141 | } |
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142 | ||
143 | /** |
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144 | * Create a new Poisson distribution with poisson parameter lambda. |
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145 | * <p> |
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146 | * lambda must be postive; otherwise an |
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147 | * <code>IllegalArgumentException</code> is thrown. |
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148 | * |
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149 | * @param lambda poisson parameter |
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150 | * @return a new Poisson distribution |
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151 | * @throws IllegalArgumentException if lambda ≤ 0 |
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152 | */ |
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153 | public PoissonDistribution createPoissonDistribution(double lambda) { |
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154 | 28 | return new PoissonDistributionImpl(lambda); |
155 | } |
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156 | ||
157 | } |