1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 18 package org.apache.commons.math.distribution; 19 20 import java.io.Serializable; 21 22 /** 23 * Default implementation of 24 * {@link org.apache.commons.math.distribution.WeibullDistribution}. 25 * 26 * @since 1.1 27 * @version $Revision: 617953 $ $Date: 2008-02-02 22:54:00 -0700 (Sat, 02 Feb 2008) $ 28 */ 29 public class WeibullDistributionImpl extends AbstractContinuousDistribution 30 implements WeibullDistribution, Serializable { 31 32 /** Serializable version identifier */ 33 private static final long serialVersionUID = 8589540077390120676L; 34 35 /** The shape parameter. */ 36 private double alpha; 37 38 /** The scale parameter. */ 39 private double beta; 40 41 /** 42 * Creates weibull distribution with the given shape and scale and a 43 * location equal to zero. 44 * @param alpha the shape parameter. 45 * @param beta the scale parameter. 46 */ 47 public WeibullDistributionImpl(double alpha, double beta){ 48 super(); 49 setShape(alpha); 50 setScale(beta); 51 } 52 53 /** 54 * For this disbution, X, this method returns P(X < <code>x</code>). 55 * @param x the value at which the CDF is evaluated. 56 * @return CDF evaluted at <code>x</code>. 57 */ 58 public double cumulativeProbability(double x) { 59 double ret; 60 if (x <= 0.0) { 61 ret = 0.0; 62 } else { 63 ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape())); 64 } 65 return ret; 66 } 67 68 /** 69 * Access the shape parameter. 70 * @return the shape parameter. 71 */ 72 public double getShape() { 73 return alpha; 74 } 75 76 /** 77 * Access the scale parameter. 78 * @return the scale parameter. 79 */ 80 public double getScale() { 81 return beta; 82 } 83 84 /** 85 * For this distribution, X, this method returns the critical point x, such 86 * that P(X < x) = <code>p</code>. 87 * <p> 88 * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 89 * <code>Double.POSITIVE_INFINITY</code> for p=1.</p> 90 * 91 * @param p the desired probability 92 * @return x, such that P(X < x) = <code>p</code> 93 * @throws IllegalArgumentException if <code>p</code> is not a valid 94 * probability. 95 */ 96 public double inverseCumulativeProbability(double p) { 97 double ret; 98 if (p < 0.0 || p > 1.0) { 99 throw new IllegalArgumentException 100 ("probability argument must be between 0 and 1 (inclusive)"); 101 } else if (p == 0) { 102 ret = 0.0; 103 } else if (p == 1) { 104 ret = Double.POSITIVE_INFINITY; 105 } else { 106 ret = getScale() * Math.pow(-Math.log(1.0 - p), 1.0 / getShape()); 107 } 108 return ret; 109 } 110 111 /** 112 * Modify the shape parameter. 113 * @param alpha the new shape parameter value. 114 */ 115 public void setShape(double alpha) { 116 if (alpha <= 0.0) { 117 throw new IllegalArgumentException( 118 "Shape must be positive."); 119 } 120 this.alpha = alpha; 121 } 122 123 /** 124 * Modify the scale parameter. 125 * @param beta the new scale parameter value. 126 */ 127 public void setScale(double beta) { 128 if (beta <= 0.0) { 129 throw new IllegalArgumentException( 130 "Scale must be positive."); 131 } 132 this.beta = beta; 133 } 134 135 /** 136 * Access the domain value lower bound, based on <code>p</code>, used to 137 * bracket a CDF root. This method is used by 138 * {@link #inverseCumulativeProbability(double)} to find critical values. 139 * 140 * @param p the desired probability for the critical value 141 * @return domain value lower bound, i.e. 142 * P(X < <i>lower bound</i>) < <code>p</code> 143 */ 144 protected double getDomainLowerBound(double p) { 145 return 0.0; 146 } 147 148 /** 149 * Access the domain value upper bound, based on <code>p</code>, used to 150 * bracket a CDF root. This method is used by 151 * {@link #inverseCumulativeProbability(double)} to find critical values. 152 * 153 * @param p the desired probability for the critical value 154 * @return domain value upper bound, i.e. 155 * P(X < <i>upper bound</i>) > <code>p</code> 156 */ 157 protected double getDomainUpperBound(double p) { 158 return Double.MAX_VALUE; 159 } 160 161 /** 162 * Access the initial domain value, based on <code>p</code>, used to 163 * bracket a CDF root. This method is used by 164 * {@link #inverseCumulativeProbability(double)} to find critical values. 165 * 166 * @param p the desired probability for the critical value 167 * @return initial domain value 168 */ 169 protected double getInitialDomain(double p) { 170 // use median 171 return Math.pow(getScale() * Math.log(2.0), 1.0 / getShape()); 172 } 173 }