{- Chi squared test of uniformity. Given a list of counts, integers separated by whitespace on standard input, this program tests the hypothesis that they were sampled from a discrete uniform distribution. Copyright 2020 Ken Takusagawa This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . -} {-# LANGUAGE ScopedTypeVariables, PackageImports #-} module Main where { import Data.Function((&)); import Control.Category((>>>)); import Prelude hiding((.),(>>)); import qualified Data.Maybe as Maybe; import Statistics.Test.ChiSquared(chi2test,testSignificance,testStatistics); import "statistics" Statistics.Types(PValue); import qualified "vector" Data.Vector as Vector; import qualified Statistics.Test.Types as Statistics; import Statistics.Distribution.ChiSquared(ChiSquared); main :: IO(); main = do { (len,s,result) <- getContents >>= (words >>> map read >>> chi2 >>> return); putStrLn \$ "n " ++ show len; putStrLn \$ "sum " ++ show s; putStrLn \$ "chi^2 " ++ show (testStatistics result); let { pvalue :: PValue Double ; pvalue = testSignificance result }; print pvalue; -- problem with testDistribution https://github.com/bos/statistics/issues/167 }; chi2 :: [Integer] -> (Int, Integer, Statistics.Test ChiSquared); chi2 obs = let { s :: Integer; s = sum obs; len :: Int; len = length obs; expected :: Double; expected = fromInteger s / fromIntegral len; f :: Integer -> (Int,Double); f o = (fromInteger o,expected); } in (len, s, map f obs & Vector.fromList & chi2test 0 & Maybe.fromJust) ; } --end