1 | /*************************************************************************
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2 | Cephes Math Library Release 2.8: June, 2000
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3 | Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
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4 |
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5 | Contributors:
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6 | * Sergey Bochkanov (ALGLIB project). Translation from C to
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7 | pseudocode.
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8 |
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9 | See subroutines comments for additional copyrights.
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10 |
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11 | >>> SOURCE LICENSE >>>
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12 | This program is free software; you can redistribute it and/or modify
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13 | it under the terms of the GNU General Public License as published by
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14 | the Free Software Foundation (www.fsf.org); either version 2 of the
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15 | License, or (at your option) any later version.
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16 |
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17 | This program is distributed in the hope that it will be useful,
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18 | but WITHOUT ANY WARRANTY; without even the implied warranty of
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19 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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20 | GNU General Public License for more details.
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21 |
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22 | A copy of the GNU General Public License is available at
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23 | http://www.fsf.org/licensing/licenses
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24 |
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25 | >>> END OF LICENSE >>>
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26 | *************************************************************************/
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27 |
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28 | using System;
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29 |
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30 | namespace alglib
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31 | {
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32 | public class fdistr
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33 | {
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34 | /*************************************************************************
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35 | F distribution
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36 |
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37 | Returns the area from zero to x under the F density
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38 | function (also known as Snedcor's density or the
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39 | variance ratio density). This is the density
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40 | of x = (u1/df1)/(u2/df2), where u1 and u2 are random
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41 | variables having Chi square distributions with df1
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42 | and df2 degrees of freedom, respectively.
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43 | The incomplete beta integral is used, according to the
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44 | formula
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45 |
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46 | P(x) = incbet( df1/2, df2/2, (df1*x/(df2 + df1*x) ).
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47 |
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48 |
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49 | The arguments a and b are greater than zero, and x is
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50 | nonnegative.
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51 |
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52 | ACCURACY:
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53 |
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54 | Tested at random points (a,b,x).
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55 |
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56 | x a,b Relative error:
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57 | arithmetic domain domain # trials peak rms
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58 | IEEE 0,1 0,100 100000 9.8e-15 1.7e-15
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59 | IEEE 1,5 0,100 100000 6.5e-15 3.5e-16
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60 | IEEE 0,1 1,10000 100000 2.2e-11 3.3e-12
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61 | IEEE 1,5 1,10000 100000 1.1e-11 1.7e-13
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62 |
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63 | Cephes Math Library Release 2.8: June, 2000
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64 | Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
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65 | *************************************************************************/
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66 | public static double fdistribution(int a,
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67 | int b,
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68 | double x)
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69 | {
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70 | double result = 0;
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71 | double w = 0;
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72 |
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73 | System.Diagnostics.Debug.Assert(a>=1 & b>=1 & (double)(x)>=(double)(0), "Domain error in FDistribution");
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74 | w = a*x;
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75 | w = w/(b+w);
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76 | result = ibetaf.incompletebeta(0.5*a, 0.5*b, w);
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77 | return result;
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78 | }
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79 |
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80 |
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81 | /*************************************************************************
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82 | Complemented F distribution
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83 |
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84 | Returns the area from x to infinity under the F density
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85 | function (also known as Snedcor's density or the
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86 | variance ratio density).
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87 |
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88 |
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89 | inf.
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90 | -
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91 | 1 | | a-1 b-1
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92 | 1-P(x) = ------ | t (1-t) dt
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93 | B(a,b) | |
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94 | -
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95 | x
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96 |
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97 |
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98 | The incomplete beta integral is used, according to the
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99 | formula
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100 |
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101 | P(x) = incbet( df2/2, df1/2, (df2/(df2 + df1*x) ).
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102 |
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103 |
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104 | ACCURACY:
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105 |
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106 | Tested at random points (a,b,x) in the indicated intervals.
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107 | x a,b Relative error:
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108 | arithmetic domain domain # trials peak rms
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109 | IEEE 0,1 1,100 100000 3.7e-14 5.9e-16
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110 | IEEE 1,5 1,100 100000 8.0e-15 1.6e-15
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111 | IEEE 0,1 1,10000 100000 1.8e-11 3.5e-13
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112 | IEEE 1,5 1,10000 100000 2.0e-11 3.0e-12
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113 |
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114 | Cephes Math Library Release 2.8: June, 2000
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115 | Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
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116 | *************************************************************************/
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117 | public static double fcdistribution(int a,
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118 | int b,
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119 | double x)
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120 | {
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121 | double result = 0;
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122 | double w = 0;
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123 |
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124 | System.Diagnostics.Debug.Assert(a>=1 & b>=1 & (double)(x)>=(double)(0), "Domain error in FCDistribution");
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125 | w = b/(b+a*x);
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126 | result = ibetaf.incompletebeta(0.5*b, 0.5*a, w);
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127 | return result;
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128 | }
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129 |
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130 |
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131 | /*************************************************************************
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132 | Inverse of complemented F distribution
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133 |
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134 | Finds the F density argument x such that the integral
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135 | from x to infinity of the F density is equal to the
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136 | given probability p.
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137 |
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138 | This is accomplished using the inverse beta integral
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139 | function and the relations
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140 |
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141 | z = incbi( df2/2, df1/2, p )
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142 | x = df2 (1-z) / (df1 z).
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143 |
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144 | Note: the following relations hold for the inverse of
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145 | the uncomplemented F distribution:
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146 |
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147 | z = incbi( df1/2, df2/2, p )
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148 | x = df2 z / (df1 (1-z)).
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149 |
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150 | ACCURACY:
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151 |
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152 | Tested at random points (a,b,p).
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153 |
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154 | a,b Relative error:
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155 | arithmetic domain # trials peak rms
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156 | For p between .001 and 1:
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157 | IEEE 1,100 100000 8.3e-15 4.7e-16
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158 | IEEE 1,10000 100000 2.1e-11 1.4e-13
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159 | For p between 10^-6 and 10^-3:
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160 | IEEE 1,100 50000 1.3e-12 8.4e-15
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161 | IEEE 1,10000 50000 3.0e-12 4.8e-14
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162 |
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163 | Cephes Math Library Release 2.8: June, 2000
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164 | Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
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165 | *************************************************************************/
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166 | public static double invfdistribution(int a,
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167 | int b,
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168 | double y)
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169 | {
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170 | double result = 0;
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171 | double w = 0;
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172 | double x = 0;
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173 |
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174 | System.Diagnostics.Debug.Assert(a>=1 & b>=1 & (double)(y)>(double)(0) & (double)(y)<=(double)(1), "Domain error in InvFDistribution");
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175 |
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176 | //
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177 | // Compute probability for x = 0.5
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178 | //
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179 | w = ibetaf.incompletebeta(0.5*b, 0.5*a, 0.5);
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180 |
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181 | //
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182 | // If that is greater than y, then the solution w < .5
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183 | // Otherwise, solve at 1-y to remove cancellation in (b - b*w)
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184 | //
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185 | if( (double)(w)>(double)(y) | (double)(y)<(double)(0.001) )
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186 | {
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187 | w = ibetaf.invincompletebeta(0.5*b, 0.5*a, y);
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188 | result = (b-b*w)/(a*w);
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189 | }
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190 | else
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191 | {
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192 | w = ibetaf.invincompletebeta(0.5*a, 0.5*b, 1.0-y);
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193 | result = b*w/(a*(1.0-w));
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194 | }
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195 | return result;
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196 | }
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197 | }
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198 | }
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