WIP: Kolmogorov-Smirnov test

src/FSharp.Stats/FSharp.Stats.fsproj

@@ -115,6 +115,7 @@
     <Compile Include="Testing\FTest.fs" />
     <Compile Include="Testing\FriedmanTest.fs" />
     <Compile Include="Testing\HTest.fs" />
+    <Compile Include="Testing\KolmogorovSmirnov.fs" />
     <Compile Include="Testing\ChiSquareTest.fs" />
     <Compile Include="Testing\Bartlett.fs" />
     <Compile Include="Testing\PostHoc.fs" />

src/FSharp.Stats/Testing/KolmogorovSmirnov.fs

@@ -0,0 +1,21 @@
+namespace FSharp.Stats.Testing
+
+open FSharp.Stats.Distributions
+
+module KolmogorovSmirnov =
+
+    /// Tests the input values with the Kolmogorov-Smirnov Goodness of Fit-test against a normal distribution and returns a p-Value. 
+    /// The p-value indicates how likely it is to observe such a distribution under the assumption that the null hypothesis is true (= sample distribution normally distributed).  
+    /// In short: The lower the p-value, the more likely it is that the sample does NOT originate from a normal distribution.
+    let goF values =
+        let lVals = Array.length values |> float
+        let rankedVals = Array.sort values
+        let rankedNormVals = rankedVals |> Array.mapi (fun i _ -> float i / lVals)
+        let meanVals = FSharp.Stats.Seq.mean values
+        let stdVals = FSharp.Stats.Seq.stDev values
+        let nD = FSharp.Stats.Distributions.Continuous.normal meanVals stdVals
+        let cum = rankedVals |> Array.map (fun v -> nD.CDF v)
+        let deltaCumVals = (cum, rankedNormVals) ||> Array.map2 (fun c v -> System.Math.Abs (c - v))
+        let kS = Array.max deltaCumVals
+        kS
+        Continuous.kolmogorov