001 /* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017 018 package org.apache.commons.math.distribution; 019 020 import java.io.Serializable; 021 022 import org.apache.commons.math.MathRuntimeException; 023 024 /** 025 * Default implementation of 026 * {@link org.apache.commons.math.distribution.WeibullDistribution}. 027 * 028 * @since 1.1 029 * @version $Revision: 772119 $ $Date: 2009-05-06 05:43:28 -0400 (Wed, 06 May 2009) $ 030 */ 031 public class WeibullDistributionImpl extends AbstractContinuousDistribution 032 implements WeibullDistribution, Serializable { 033 034 /** Serializable version identifier */ 035 private static final long serialVersionUID = 8589540077390120676L; 036 037 /** The shape parameter. */ 038 private double alpha; 039 040 /** The scale parameter. */ 041 private double beta; 042 043 /** 044 * Creates weibull distribution with the given shape and scale and a 045 * location equal to zero. 046 * @param alpha the shape parameter. 047 * @param beta the scale parameter. 048 */ 049 public WeibullDistributionImpl(double alpha, double beta){ 050 super(); 051 setShape(alpha); 052 setScale(beta); 053 } 054 055 /** 056 * For this distribution, X, this method returns P(X < <code>x</code>). 057 * @param x the value at which the CDF is evaluated. 058 * @return CDF evaluted at <code>x</code>. 059 */ 060 public double cumulativeProbability(double x) { 061 double ret; 062 if (x <= 0.0) { 063 ret = 0.0; 064 } else { 065 ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape())); 066 } 067 return ret; 068 } 069 070 /** 071 * Access the shape parameter. 072 * @return the shape parameter. 073 */ 074 public double getShape() { 075 return alpha; 076 } 077 078 /** 079 * Access the scale parameter. 080 * @return the scale parameter. 081 */ 082 public double getScale() { 083 return beta; 084 } 085 086 /** 087 * For this distribution, X, this method returns the critical point x, such 088 * that P(X < x) = <code>p</code>. 089 * <p> 090 * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 091 * <code>Double.POSITIVE_INFINITY</code> for p=1.</p> 092 * 093 * @param p the desired probability 094 * @return x, such that P(X < x) = <code>p</code> 095 * @throws IllegalArgumentException if <code>p</code> is not a valid 096 * probability. 097 */ 098 @Override 099 public double inverseCumulativeProbability(double p) { 100 double ret; 101 if (p < 0.0 || p > 1.0) { 102 throw MathRuntimeException.createIllegalArgumentException( 103 "{0} out of [{1}, {2}] range", p, 0.0, 1.0); 104 } else if (p == 0) { 105 ret = 0.0; 106 } else if (p == 1) { 107 ret = Double.POSITIVE_INFINITY; 108 } else { 109 ret = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape()); 110 } 111 return ret; 112 } 113 114 /** 115 * Modify the shape parameter. 116 * @param alpha the new shape parameter value. 117 */ 118 public void setShape(double alpha) { 119 if (alpha <= 0.0) { 120 throw MathRuntimeException.createIllegalArgumentException( 121 "shape must be positive ({0})", 122 alpha); 123 } 124 this.alpha = alpha; 125 } 126 127 /** 128 * Modify the scale parameter. 129 * @param beta the new scale parameter value. 130 */ 131 public void setScale(double beta) { 132 if (beta <= 0.0) { 133 throw MathRuntimeException.createIllegalArgumentException( 134 "scale must be positive ({0})", 135 beta); 136 } 137 this.beta = beta; 138 } 139 140 /** 141 * Access the domain value lower bound, based on <code>p</code>, used to 142 * bracket a CDF root. This method is used by 143 * {@link #inverseCumulativeProbability(double)} to find critical values. 144 * 145 * @param p the desired probability for the critical value 146 * @return domain value lower bound, i.e. 147 * P(X < <i>lower bound</i>) < <code>p</code> 148 */ 149 @Override 150 protected double getDomainLowerBound(double p) { 151 return 0.0; 152 } 153 154 /** 155 * Access the domain value upper bound, based on <code>p</code>, used to 156 * bracket a CDF root. This method is used by 157 * {@link #inverseCumulativeProbability(double)} to find critical values. 158 * 159 * @param p the desired probability for the critical value 160 * @return domain value upper bound, i.e. 161 * P(X < <i>upper bound</i>) > <code>p</code> 162 */ 163 @Override 164 protected double getDomainUpperBound(double p) { 165 return Double.MAX_VALUE; 166 } 167 168 /** 169 * Access the initial domain value, based on <code>p</code>, used to 170 * bracket a CDF root. This method is used by 171 * {@link #inverseCumulativeProbability(double)} to find critical values. 172 * 173 * @param p the desired probability for the critical value 174 * @return initial domain value 175 */ 176 @Override 177 protected double getInitialDomain(double p) { 178 // use median 179 return Math.pow(getScale() * Math.log(2.0), 1.0 / getShape()); 180 } 181 }