1 /* 2 * Copyright 2005 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 17 package org.apache.commons.math.distribution; 18 19 import java.io.Serializable; 20 21 /** 22 * Default implementation of 23 * {@link org.apache.commons.math.distribution.WeibullDistribution}. 24 * 25 * @since 1.1 26 * @version $Revision: 1.13 $ $Date: 2004-07-24 16:41:37 -0500 (Sat, 24 Jul 2004) $ 27 */ 28 public class WeibullDistributionImpl extends AbstractContinuousDistribution 29 implements WeibullDistribution, Serializable { 30 31 /** Serializable version identifier */ 32 private static final long serialVersionUID = 8589540077390120676L; 33 34 /** The shape parameter. */ 35 private double alpha; 36 37 /** The scale parameter. */ 38 private double beta; 39 40 /** 41 * Creates weibull distribution with the given shape and scale and a 42 * location equal to zero. 43 * @param alpha the shape parameter. 44 * @param beta the scale parameter. 45 */ 46 public WeibullDistributionImpl(double alpha, double beta){ 47 super(); 48 setShape(alpha); 49 setScale(beta); 50 } 51 52 /** 53 * For this disbution, X, this method returns P(X < <code>x</code>). 54 * @param x the value at which the CDF is evaluated. 55 * @return CDF evaluted at <code>x</code>. 56 */ 57 public double cumulativeProbability(double x) { 58 double ret; 59 if (x <= 0.0) { 60 ret = 0.0; 61 } else { 62 ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape())); 63 } 64 return ret; 65 } 66 67 /** 68 * Access the shape parameter. 69 * @return the shape parameter. 70 */ 71 public double getShape() { 72 return alpha; 73 } 74 75 /** 76 * Access the scale parameter. 77 * @return the scale parameter. 78 */ 79 public double getScale() { 80 return beta; 81 } 82 83 /** 84 * For this distribution, X, this method returns the critical point x, such 85 * that P(X < x) = <code>p</code>. 86 * <p> 87 * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 88 * <code>Double.POSITIVE_INFINITY</code> for p=1. 89 * 90 * @param p the desired probability 91 * @return x, such that P(X < x) = <code>p</code> 92 * @throws IllegalArgumentException if <code>p</code> is not a valid 93 * probability. 94 */ 95 public double inverseCumulativeProbability(double p) { 96 double ret; 97 if (p < 0.0 || p > 1.0) { 98 throw new IllegalArgumentException 99 ("probability argument must be between 0 and 1 (inclusive)"); 100 } else if (p == 0) { 101 ret = 0.0; 102 } else if (p == 1) { 103 ret = Double.POSITIVE_INFINITY; 104 } else { 105 ret = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape()); 106 } 107 return ret; 108 } 109 110 /** 111 * Modify the shape parameter. 112 * @param alpha the new shape parameter value. 113 */ 114 public void setShape(double alpha) { 115 if (alpha <= 0.0) { 116 throw new IllegalArgumentException( 117 "Shape must be positive."); 118 } 119 this.alpha = alpha; 120 } 121 122 /** 123 * Modify the scale parameter. 124 * @param beta the new scale parameter value. 125 */ 126 public void setScale(double beta) { 127 if (beta <= 0.0) { 128 throw new IllegalArgumentException( 129 "Scale must be positive."); 130 } 131 this.beta = beta; 132 } 133 134 /** 135 * Access the domain value lower bound, based on <code>p</code>, used to 136 * bracket a CDF root. This method is used by 137 * {@link #inverseCumulativeProbability(double)} to find critical values. 138 * 139 * @param p the desired probability for the critical value 140 * @return domain value lower bound, i.e. 141 * P(X < <i>lower bound</i>) < <code>p</code> 142 */ 143 protected double getDomainLowerBound(double p) { 144 return 0.0; 145 } 146 147 /** 148 * Access the domain value upper bound, based on <code>p</code>, used to 149 * bracket a CDF root. This method is used by 150 * {@link #inverseCumulativeProbability(double)} to find critical values. 151 * 152 * @param p the desired probability for the critical value 153 * @return domain value upper bound, i.e. 154 * P(X < <i>upper bound</i>) > <code>p</code> 155 */ 156 protected double getDomainUpperBound(double p) { 157 return Double.MAX_VALUE; 158 } 159 160 /** 161 * Access the initial domain value, based on <code>p</code>, used to 162 * bracket a CDF root. This method is used by 163 * {@link #inverseCumulativeProbability(double)} to find critical values. 164 * 165 * @param p the desired probability for the critical value 166 * @return initial domain value 167 */ 168 protected double getInitialDomain(double p) { 169 // use median 170 return Math.pow(getScale() * Math.log(2.0), 1.0 / getShape()); 171 } 172 }