1 | /*
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2 | * Licensed to the Apache Software Foundation (ASF) under one or more
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3 | * contributor license agreements. See the NOTICE file distributed with
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4 | * this work for additional information regarding copyright ownership.
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5 | * The ASF licenses this file to You under the Apache License, Version 2.0
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6 | * (the "License"); you may not use this file except in compliance with
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7 | * the License. You may obtain a copy of the License at
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8 | *
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9 | * http://www.apache.org/licenses/LICENSE-2.0
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10 | *
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11 | * Unless required by applicable law or agreed to in writing, software
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12 | * distributed under the License is distributed on an "AS IS" BASIS,
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13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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14 | * See the License for the specific language governing permissions and
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15 | * limitations under the License.
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16 | */
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17 |
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18 | package agents.org.apache.commons.math.distribution;
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19 |
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20 | import java.io.Serializable;
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21 |
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22 | import agents.org.apache.commons.math.MathRuntimeException;
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23 | import agents.org.apache.commons.math.exception.util.LocalizedFormats;
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24 | import agents.org.apache.commons.math.util.FastMath;
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25 |
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26 | /**
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27 | * Default implementation of
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28 | * {@link agents.org.apache.commons.math.distribution.CauchyDistribution}.
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29 | *
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30 | * @since 1.1
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31 | * @version $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
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32 | */
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33 | public class CauchyDistributionImpl extends AbstractContinuousDistribution
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34 | implements CauchyDistribution, Serializable {
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35 |
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36 | /**
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37 | * Default inverse cumulative probability accuracy
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38 | * @since 2.1
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39 | */
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40 | public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
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41 |
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42 | /** Serializable version identifier */
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43 | private static final long serialVersionUID = 8589540077390120676L;
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44 |
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45 | /** The median of this distribution. */
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46 | private double median = 0;
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47 |
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48 | /** The scale of this distribution. */
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49 | private double scale = 1;
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50 |
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51 | /** Inverse cumulative probability accuracy */
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52 | private final double solverAbsoluteAccuracy;
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53 |
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54 | /**
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55 | * Creates cauchy distribution with the medain equal to zero and scale
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56 | * equal to one.
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57 | */
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58 | public CauchyDistributionImpl(){
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59 | this(0.0, 1.0);
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60 | }
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61 |
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62 | /**
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63 | * Create a cauchy distribution using the given median and scale.
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64 | * @param median median for this distribution
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65 | * @param s scale parameter for this distribution
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66 | */
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67 | public CauchyDistributionImpl(double median, double s){
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68 | this(median, s, DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
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69 | }
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70 |
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71 | /**
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72 | * Create a cauchy distribution using the given median and scale.
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73 | * @param median median for this distribution
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74 | * @param s scale parameter for this distribution
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75 | * @param inverseCumAccuracy the maximum absolute error in inverse cumulative probability estimates
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76 | * (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY})
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77 | * @since 2.1
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78 | */
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79 | public CauchyDistributionImpl(double median, double s, double inverseCumAccuracy) {
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80 | super();
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81 | setMedianInternal(median);
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82 | setScaleInternal(s);
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83 | solverAbsoluteAccuracy = inverseCumAccuracy;
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84 | }
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85 |
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86 | /**
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87 | * For this distribution, X, this method returns P(X < <code>x</code>).
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88 | * @param x the value at which the CDF is evaluated.
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89 | * @return CDF evaluated at <code>x</code>.
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90 | */
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91 | public double cumulativeProbability(double x) {
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92 | return 0.5 + (FastMath.atan((x - median) / scale) / FastMath.PI);
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93 | }
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94 |
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95 | /**
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96 | * Access the median.
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97 | * @return median for this distribution
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98 | */
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99 | public double getMedian() {
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100 | return median;
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101 | }
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102 |
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103 | /**
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104 | * Access the scale parameter.
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105 | * @return scale parameter for this distribution
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106 | */
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107 | public double getScale() {
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108 | return scale;
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109 | }
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110 |
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111 | /**
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112 | * Returns the probability density for a particular point.
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113 | *
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114 | * @param x The point at which the density should be computed.
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115 | * @return The pdf at point x.
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116 | * @since 2.1
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117 | */
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118 | @Override
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119 | public double density(double x) {
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120 | final double dev = x - median;
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121 | return (1 / FastMath.PI) * (scale / (dev * dev + scale * scale));
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122 | }
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123 |
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124 | /**
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125 | * For this distribution, X, this method returns the critical point x, such
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126 | * that P(X < x) = <code>p</code>.
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127 | * <p>
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128 | * Returns <code>Double.NEGATIVE_INFINITY</code> for p=0 and
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129 | * <code>Double.POSITIVE_INFINITY</code> for p=1.</p>
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130 | *
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131 | * @param p the desired probability
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132 | * @return x, such that P(X < x) = <code>p</code>
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133 | * @throws IllegalArgumentException if <code>p</code> is not a valid
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134 | * probability.
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135 | */
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136 | @Override
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137 | public double inverseCumulativeProbability(double p) {
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138 | double ret;
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139 | if (p < 0.0 || p > 1.0) {
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140 | throw MathRuntimeException.createIllegalArgumentException(
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141 | LocalizedFormats.OUT_OF_RANGE_SIMPLE, p, 0.0, 1.0);
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142 | } else if (p == 0) {
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143 | ret = Double.NEGATIVE_INFINITY;
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144 | } else if (p == 1) {
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145 | ret = Double.POSITIVE_INFINITY;
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146 | } else {
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147 | ret = median + scale * FastMath.tan(FastMath.PI * (p - .5));
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148 | }
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149 | return ret;
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150 | }
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151 |
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152 | /**
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153 | * Modify the median.
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154 | * @param median for this distribution
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155 | * @deprecated as of 2.1 (class will become immutable in 3.0)
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156 | */
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157 | @Deprecated
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158 | public void setMedian(double median) {
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159 | setMedianInternal(median);
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160 | }
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161 |
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162 | /**
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163 | * Modify the median.
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164 | * @param newMedian for this distribution
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165 | */
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166 | private void setMedianInternal(double newMedian) {
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167 | this.median = newMedian;
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168 | }
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169 |
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170 | /**
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171 | * Modify the scale parameter.
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172 | * @param s scale parameter for this distribution
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173 | * @throws IllegalArgumentException if <code>sd</code> is not positive.
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174 | * @deprecated as of 2.1 (class will become immutable in 3.0)
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175 | */
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176 | @Deprecated
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177 | public void setScale(double s) {
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178 | setScaleInternal(s);
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179 | }
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180 |
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181 | /**
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182 | * Modify the scale parameter.
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183 | * @param s scale parameter for this distribution
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184 | * @throws IllegalArgumentException if <code>sd</code> is not positive.
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185 | */
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186 | private void setScaleInternal(double s) {
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187 | if (s <= 0.0) {
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188 | throw MathRuntimeException.createIllegalArgumentException(
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189 | LocalizedFormats.NOT_POSITIVE_SCALE, s);
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190 | }
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191 | scale = s;
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192 | }
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193 |
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194 | /**
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195 | * Access the domain value lower bound, based on <code>p</code>, used to
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196 | * bracket a CDF root. This method is used by
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197 | * {@link #inverseCumulativeProbability(double)} to find critical values.
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198 | *
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199 | * @param p the desired probability for the critical value
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200 | * @return domain value lower bound, i.e.
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201 | * P(X < <i>lower bound</i>) < <code>p</code>
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202 | */
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203 | @Override
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204 | protected double getDomainLowerBound(double p) {
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205 | double ret;
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206 |
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207 | if (p < .5) {
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208 | ret = -Double.MAX_VALUE;
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209 | } else {
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210 | ret = median;
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211 | }
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212 |
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213 | return ret;
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214 | }
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215 |
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216 | /**
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217 | * Access the domain value upper bound, based on <code>p</code>, used to
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218 | * bracket a CDF root. This method is used by
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219 | * {@link #inverseCumulativeProbability(double)} to find critical values.
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220 | *
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221 | * @param p the desired probability for the critical value
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222 | * @return domain value upper bound, i.e.
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223 | * P(X < <i>upper bound</i>) > <code>p</code>
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224 | */
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225 | @Override
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226 | protected double getDomainUpperBound(double p) {
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227 | double ret;
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228 |
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229 | if (p < .5) {
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230 | ret = median;
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231 | } else {
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232 | ret = Double.MAX_VALUE;
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233 | }
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234 |
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235 | return ret;
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236 | }
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237 |
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238 | /**
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239 | * Access the initial domain value, based on <code>p</code>, used to
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240 | * bracket a CDF root. This method is used by
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241 | * {@link #inverseCumulativeProbability(double)} to find critical values.
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242 | *
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243 | * @param p the desired probability for the critical value
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244 | * @return initial domain value
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245 | */
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246 | @Override
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247 | protected double getInitialDomain(double p) {
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248 | double ret;
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249 |
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250 | if (p < .5) {
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251 | ret = median - scale;
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252 | } else if (p > .5) {
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253 | ret = median + scale;
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254 | } else {
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255 | ret = median;
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256 | }
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257 |
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258 | return ret;
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259 | }
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260 |
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261 | /**
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262 | * Return the absolute accuracy setting of the solver used to estimate
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263 | * inverse cumulative probabilities.
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264 | *
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265 | * @return the solver absolute accuracy
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266 | * @since 2.1
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267 | */
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268 | @Override
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269 | protected double getSolverAbsoluteAccuracy() {
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270 | return solverAbsoluteAccuracy;
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271 | }
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272 |
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273 | /**
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274 | * Returns the lower bound of the support for this distribution.
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275 | * The lower bound of the support of the Cauchy distribution is always
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276 | * negative infinity, regardless of the parameters.
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277 | *
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278 | * @return lower bound of the support (always Double.NEGATIVE_INFINITY)
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279 | * @since 2.2
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280 | */
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281 | public double getSupportLowerBound() {
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282 | return Double.NEGATIVE_INFINITY;
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283 | }
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284 |
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285 | /**
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286 | * Returns the upper bound of the support for this distribution.
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287 | * The upper bound of the support of the Cauchy distribution is always
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288 | * positive infinity, regardless of the parameters.
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289 | *
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290 | * @return upper bound of the support (always Double.POSITIVE_INFINITY)
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291 | * @since 2.2
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292 | */
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293 | public double getSupportUpperBound() {
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294 | return Double.POSITIVE_INFINITY;
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295 | }
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296 |
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297 | /**
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298 | * Returns the mean.
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299 | *
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300 | * The mean is always undefined, regardless of the parameters.
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301 | *
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302 | * @return mean (always Double.NaN)
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303 | * @since 2.2
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304 | */
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305 | public double getNumericalMean() {
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306 | return Double.NaN;
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307 | }
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308 |
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309 | /**
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310 | * Returns the variance.
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311 | *
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312 | * The variance is always undefined, regardless of the parameters.
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313 | *
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314 | * @return variance (always Double.NaN)
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315 | * @since 2.2
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316 | */
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317 | public double getNumericalVariance() {
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318 | return Double.NaN;
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319 | }
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320 | }
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