lib/statistics/distribution/normal.rb in ruby-statistics-2.1.0 vs lib/statistics/distribution/normal.rb in ruby-statistics-2.1.1

- old
+ new

@@ -77,7 +77,63 @@ euler = Math.exp(-pow) euler/Math.sqrt(2 * Math::PI) end end + + # Inverse Standard Normal distribution: + # References: + # https://en.wikipedia.org/wiki/Inverse_distribution + # http://www.source-code.biz/snippets/vbasic/9.htm + class InverseStandardNormal < StandardNormal + A1 = -39.6968302866538 + A2 = 220.946098424521 + A3 = -275.928510446969 + A4 = 138.357751867269 + A5 = -30.6647980661472 + A6 = 2.50662827745924 + B1 = -54.4760987982241 + B2 = 161.585836858041 + B3 = -155.698979859887 + B4 = 66.8013118877197 + B5 = -13.2806815528857 + C1 = -7.78489400243029E-03 + C2 = -0.322396458041136 + C3 = -2.40075827716184 + C4 = -2.54973253934373 + C5 = 4.37466414146497 + C6 = 2.93816398269878 + D1 = 7.78469570904146E-03 + D2 = 0.32246712907004 + D3 = 2.445134137143 + D4 = 3.75440866190742 + P_LOW = 0.02425 + P_HIGH = 1 - P_LOW + + def density_function(_) + raise NotImplementedError + end + + def random(elements: 1, seed: Random.new_seed) + raise NotImplementedError + end + + def cumulative_function(value) + return if value < 0.0 || value > 1.0 + return -1.0 * Float::INFINITY if value.zero? + return Float::INFINITY if value == 1.0 + + if value < P_LOW + q = Math.sqrt((Math.log(value) * -2.0)) + (((((C1 * q + C2) * q + C3) * q + C4) * q + C5) * q + C6) / ((((D1 * q + D2) * q + D3) * q + D4) * q + 1.0) + elsif value <= P_HIGH + q = value - 0.5 + r = q ** 2 + (((((A1 * r + A2) * r + A3) * r + A4) * r + A5) * r + A6) * q / (((((B1 * r + B2) * r + B3) * r + B4) * r + B5) * r + 1.0) + else + q = Math.sqrt((Math.log(1 - value) * -2.0)) + - (((((C1 * q + C2) * q + C3) * q + C4) * q + C5) * q + C6) / ((((D1 * q + D2) * q + D3) * q + D4) * q + 1) + end + end + end end end