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Contents
require File.expand_path(File.join(File.dirname(__FILE__), '..', '..', 'fathom')) class Fathom::Distributions::DiscreteGaussian extend Fathom::Distributions::SharedMethods class << self def rng @rng ||= GSL::Rng.alloc(GSL::Rng::MT19937_1999, Kernel.rand(100_000)) end def rand(sd) (rng.gaussian(sd) / size).floor + 1 end def inverse_cdf(opts={}) mean = opts[:mean] sd = opts[:sd] sd ||= opts[:std] sd ||= opts[:standard_deviation] lower = opts.fetch(:lower, true) lower = false if opts[:upper] confidence_interval = opts.fetch(:confidence_interval, 0.05) value = lower ? GSL::Cdf.gaussian_Pinv(confidence_interval, sd) : GSL::Cdf.gaussian_Qinv(confidence_interval, sd) value + mean end alias :lower_bound :inverse_cdf def upper_bound(opts={}) inverse_cdf(opts.merge(:lower => false)) end def interval_values(opts={}) confidence_interval = opts.fetch(:confidence_interval, 0.9) bound = (1 - confidence_interval) / 2.0 [lower_bound(opts.merge(:confidence_interval => bound)), upper_bound(opts.merge(:confidence_interval => bound))] end # If only I had the background to explain what this is.... # I want to know how many standard deviations are expressed by the confidence interval # I can then divide the range by this number to get the standard deviation def standard_deviations_under(confidence_interval) GSL::Cdf.gaussian_Qinv((1 - confidence_interval) / 2) * 2 end end end
Version data entries
8 entries across 8 versions & 1 rubygems