dacohen/Rsquared

module Rsquared
##
  # KSTest implements the Kolomogorov-Smirnov test for normality
  # kstest = Rsquared::KSTest.new(data)
  # kstest.normal? => Boolean, indicates normality of data at 5% confidence
  # 

  class KSTest
      ##
    # Intitializes the test object with an array of numerical data
    #

      def initialize(data)
        @data = data.std.sort!
        fn = 0
        d = []
        range = @data.max - @data.min
        @data.each_with_index do |x, i|
            # Calculate Fn
        fn = i + 1
        d[i] = fn/@data.length.to_f - Distribution::Normal::cdf(x)
        fn = 0.0
        end
        @ksstat = d.max
        return @ksstat
     end
     
     ##
     # Returns a boolean indiciating the significance of the test a the 5% level
     #

     def significant?
         if @ksstat > Helper::kscv(@data.length) then
             return true
         else
        return false
         end
     end

     ##
     # Returns logical opposite of significance
     #

     def normal?
         !self.significant?
     end

     def inspect
         significant?
     end
     
     ##
     # Returns the test statistic
     #

     def statistic
         @ksstat
     end
  end
end