Classes in this File | Line Coverage | Branch Coverage | Complexity | ||||||||
AbstractContinuousDistribution |
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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 | import java.io.Serializable; |
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19 | ||
20 | import org.apache.commons.math.ConvergenceException; |
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21 | import org.apache.commons.math.FunctionEvaluationException; |
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22 | import org.apache.commons.math.MathException; |
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23 | import org.apache.commons.math.analysis.UnivariateRealFunction; |
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24 | import org.apache.commons.math.analysis.UnivariateRealSolverUtils; |
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25 | ||
26 | /** |
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27 | * Base class for continuous distributions. Default implementations are |
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28 | * provided for some of the methods that do not vary from distribution to |
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29 | * distribution. |
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30 | * |
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31 | * @version $Revision$ $Date: 2005-02-26 05:11:52 -0800 (Sat, 26 Feb 2005) $ |
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32 | */ |
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33 | public abstract class AbstractContinuousDistribution |
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34 | extends AbstractDistribution |
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35 | implements ContinuousDistribution, Serializable { |
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36 | ||
37 | /** Serializable version identifier */ |
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38 | static final long serialVersionUID = -38038050983108802L; |
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39 | ||
40 | /** |
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41 | * Default constructor. |
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42 | */ |
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43 | protected AbstractContinuousDistribution() { |
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44 | 546 | super(); |
45 | 546 | } |
46 | ||
47 | /** |
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48 | * For this distribution, X, this method returns the critical point x, such |
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49 | * that P(X < x) = <code>p</code>. |
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50 | * |
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51 | * @param p the desired probability |
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52 | * @return x, such that P(X < x) = <code>p</code> |
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53 | * @throws MathException if the inverse cumulative probability can not be |
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54 | * computed due to convergence or other numerical errors. |
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55 | * @throws IllegalArgumentException if <code>p</code> is not a valid |
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56 | * probability. |
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57 | */ |
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58 | public double inverseCumulativeProbability(final double p) |
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59 | throws MathException { |
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60 | 182 | if (p < 0.0 || p > 1.0) { |
61 | 20 | throw new IllegalArgumentException("p must be between 0.0 and 1.0, inclusive."); |
62 | } |
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63 | ||
64 | // by default, do simple root finding using bracketing and default solver. |
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65 | // subclasses can overide if there is a better method. |
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66 | 162 | UnivariateRealFunction rootFindingFunction = |
67 | new UnivariateRealFunction() { |
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68 | ||
69 | 162 | public double value(double x) throws FunctionEvaluationException { |
70 | try { |
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71 | 5494 | return cumulativeProbability(x) - p; |
72 | 0 | } catch (MathException ex) { |
73 | 0 | throw new FunctionEvaluationException |
74 | (x, "Error computing cdf", ex); |
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75 | } |
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76 | } |
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77 | }; |
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78 | ||
79 | // Try to bracket root, test domain endoints if this fails |
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80 | 162 | double lowerBound = getDomainLowerBound(p); |
81 | 162 | double upperBound = getDomainUpperBound(p); |
82 | 162 | double[] bracket = null; |
83 | try { |
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84 | 162 | bracket = UnivariateRealSolverUtils.bracket( |
85 | rootFindingFunction, getInitialDomain(p), |
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86 | lowerBound, upperBound); |
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87 | 0 | } catch (ConvergenceException ex) { |
88 | /* |
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89 | * Check domain endpoints to see if one gives value that is within |
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90 | * the default solver's defaultAbsoluteAccuracy of 0 (will be the |
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91 | * case if density has bounded support and p is 0 or 1). |
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92 | * |
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93 | * TODO: expose the default solver, defaultAbsoluteAccuracy as |
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94 | * a constant. |
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95 | */ |
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96 | 0 | if (Math.abs(rootFindingFunction.value(lowerBound)) < 1E-6) { |
97 | 0 | return lowerBound; |
98 | } |
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99 | 0 | if (Math.abs(rootFindingFunction.value(upperBound)) < 1E-6) { |
100 | 0 | return upperBound; |
101 | } |
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102 | // Failed bracket convergence was not because of corner solution |
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103 | 0 | throw new MathException(ex); |
104 | 162 | } |
105 | ||
106 | // find root |
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107 | 162 | double root = UnivariateRealSolverUtils.solve(rootFindingFunction, |
108 | bracket[0],bracket[1]); |
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109 | 162 | return root; |
110 | } |
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111 | ||
112 | /** |
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113 | * Access the initial domain value, based on <code>p</code>, used to |
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114 | * bracket a CDF root. This method is used by |
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115 | * {@link #inverseCumulativeProbability(double)} to find critical values. |
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116 | * |
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117 | * @param p the desired probability for the critical value |
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118 | * @return initial domain value |
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119 | */ |
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120 | protected abstract double getInitialDomain(double p); |
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121 | ||
122 | /** |
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123 | * Access the domain value lower bound, based on <code>p</code>, used to |
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124 | * bracket a CDF root. This method is used by |
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125 | * {@link #inverseCumulativeProbability(double)} to find critical values. |
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126 | * |
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127 | * @param p the desired probability for the critical value |
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128 | * @return domain value lower bound, i.e. |
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129 | * P(X < <i>lower bound</i>) < <code>p</code> |
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130 | */ |
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131 | protected abstract double getDomainLowerBound(double p); |
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132 | ||
133 | /** |
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134 | * Access the domain value upper bound, based on <code>p</code>, used to |
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135 | * bracket a CDF root. This method is used by |
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136 | * {@link #inverseCumulativeProbability(double)} to find critical values. |
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137 | * |
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138 | * @param p the desired probability for the critical value |
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139 | * @return domain value upper bound, i.e. |
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140 | * P(X < <i>upper bound</i>) > <code>p</code> |
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141 | */ |
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142 | protected abstract double getDomainUpperBound(double p); |
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143 | } |