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 package org.apache.commons.math.distribution; 018 019 import java.io.Serializable; 020 021 import org.apache.commons.math.MathException; 022 import org.apache.commons.math.MathRuntimeException; 023 import org.apache.commons.math.special.Beta; 024 025 /** 026 * Default implementation of 027 * {@link org.apache.commons.math.distribution.TDistribution}. 028 * 029 * @version $Revision: 772119 $ $Date: 2009-05-06 05:43:28 -0400 (Wed, 06 May 2009) $ 030 */ 031 public class TDistributionImpl 032 extends AbstractContinuousDistribution 033 implements TDistribution, Serializable { 034 035 /** Serializable version identifier */ 036 private static final long serialVersionUID = -5852615386664158222L; 037 038 /** The degrees of freedom*/ 039 private double degreesOfFreedom; 040 041 /** 042 * Create a t distribution using the given degrees of freedom. 043 * @param degreesOfFreedom the degrees of freedom. 044 */ 045 public TDistributionImpl(double degreesOfFreedom) { 046 super(); 047 setDegreesOfFreedom(degreesOfFreedom); 048 } 049 050 /** 051 * Modify the degrees of freedom. 052 * @param degreesOfFreedom the new degrees of freedom. 053 */ 054 public void setDegreesOfFreedom(double degreesOfFreedom) { 055 if (degreesOfFreedom <= 0.0) { 056 throw MathRuntimeException.createIllegalArgumentException( 057 "degrees of freedom must be positive ({0})", 058 degreesOfFreedom); 059 } 060 this.degreesOfFreedom = degreesOfFreedom; 061 } 062 063 /** 064 * Access the degrees of freedom. 065 * @return the degrees of freedom. 066 */ 067 public double getDegreesOfFreedom() { 068 return degreesOfFreedom; 069 } 070 071 /** 072 * For this distribution, X, this method returns P(X < <code>x</code>). 073 * @param x the value at which the CDF is evaluated. 074 * @return CDF evaluted at <code>x</code>. 075 * @throws MathException if the cumulative probability can not be 076 * computed due to convergence or other numerical errors. 077 */ 078 public double cumulativeProbability(double x) throws MathException{ 079 double ret; 080 if (x == 0.0) { 081 ret = 0.5; 082 } else { 083 double t = 084 Beta.regularizedBeta( 085 getDegreesOfFreedom() / (getDegreesOfFreedom() + (x * x)), 086 0.5 * getDegreesOfFreedom(), 087 0.5); 088 if (x < 0.0) { 089 ret = 0.5 * t; 090 } else { 091 ret = 1.0 - 0.5 * t; 092 } 093 } 094 095 return ret; 096 } 097 098 /** 099 * For this distribution, X, this method returns the critical point x, such 100 * that P(X < x) = <code>p</code>. 101 * <p> 102 * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and 103 * <code>Double.POSITIVE_INFINITY</code> for p=1.</p> 104 * 105 * @param p the desired probability 106 * @return x, such that P(X < x) = <code>p</code> 107 * @throws MathException if the inverse cumulative probability can not be 108 * computed due to convergence or other numerical errors. 109 * @throws IllegalArgumentException if <code>p</code> is not a valid 110 * probability. 111 */ 112 @Override 113 public double inverseCumulativeProbability(final double p) 114 throws MathException { 115 if (p == 0) { 116 return Double.NEGATIVE_INFINITY; 117 } 118 if (p == 1) { 119 return Double.POSITIVE_INFINITY; 120 } 121 return super.inverseCumulativeProbability(p); 122 } 123 124 /** 125 * Access the domain value lower bound, based on <code>p</code>, used to 126 * bracket a CDF root. This method is used by 127 * {@link #inverseCumulativeProbability(double)} to find critical values. 128 * 129 * @param p the desired probability for the critical value 130 * @return domain value lower bound, i.e. 131 * P(X < <i>lower bound</i>) < <code>p</code> 132 */ 133 @Override 134 protected double getDomainLowerBound(double p) { 135 return -Double.MAX_VALUE; 136 } 137 138 /** 139 * Access the domain value upper bound, based on <code>p</code>, used to 140 * bracket a CDF root. This method is used by 141 * {@link #inverseCumulativeProbability(double)} to find critical values. 142 * 143 * @param p the desired probability for the critical value 144 * @return domain value upper bound, i.e. 145 * P(X < <i>upper bound</i>) > <code>p</code> 146 */ 147 @Override 148 protected double getDomainUpperBound(double p) { 149 return Double.MAX_VALUE; 150 } 151 152 /** 153 * Access the initial domain value, based on <code>p</code>, used to 154 * bracket a CDF root. This method is used by 155 * {@link #inverseCumulativeProbability(double)} to find critical values. 156 * 157 * @param p the desired probability for the critical value 158 * @return initial domain value 159 */ 160 @Override 161 protected double getInitialDomain(double p) { 162 return 0.0; 163 } 164 }