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 import org.apache.commons.math.MathRuntimeException; 23 24 /** 25 * Default implementation of 26 * {@link org.apache.commons.math.distribution.WeibullDistribution}. 27 * 28 * @since 1.1 29 * @version $Revision: 772119 $ $Date: 2009-05-06 05:43:28 -0400 (Wed, 06 May 2009) $ 30 */ 31 public class WeibullDistributionImpl extends AbstractContinuousDistribution 32 implements WeibullDistribution, Serializable { 33 34 /** Serializable version identifier */ 35 private static final long serialVersionUID = 8589540077390120676L; 36 37 /** The shape parameter. */ 38 private double alpha; 39 40 /** The scale parameter. */ 41 private double beta; 42 43 /** 44 * Creates weibull distribution with the given shape and scale and a 45 * location equal to zero. 46 * @param alpha the shape parameter. 47 * @param beta the scale parameter. 48 */ 49 public WeibullDistributionImpl(double alpha, double beta){ 50 super(); 51 setShape(alpha); 52 setScale(beta); 53 } 54 55 /** 56 * For this distribution, X, this method returns P(X < <code>x</code>). 57 * @param x the value at which the CDF is evaluated. 58 * @return CDF evaluted at <code>x</code>. 59 */ 60 public double cumulativeProbability(double x) { 61 double ret; 62 if (x <= 0.0) { 63 ret = 0.0; 64 } else { 65 ret = 1.0 - Math.exp(-Math.pow(x / getScale(), getShape())); 66 } 67 return ret; 68 } 69 70 /** 71 * Access the shape parameter. 72 * @return the shape parameter. 73 */ 74 public double getShape() { 75 return alpha; 76 } 77 78 /** 79 * Access the scale parameter. 80 * @return the scale parameter. 81 */ 82 public double getScale() { 83 return beta; 84 } 85 86 /** 87 * For this distribution, X, this method returns the critical point x, such 88 * that P(X < x) = <code>p</code>. 89 * <p> 90 * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 91 * <code>Double.POSITIVE_INFINITY</code> for p=1.</p> 92 * 93 * @param p the desired probability 94 * @return x, such that P(X < x) = <code>p</code> 95 * @throws IllegalArgumentException if <code>p</code> is not a valid 96 * probability. 97 */ 98 @Override 99 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 }