anchor.diff:  
               kendallCorrFun (FSharp.Stats.Rank.rankFirst setA ) (FSharp.Stats.Rank.rankFirst setB )
   
  +        /// Biweighted Midcorrelation. This is a median based correlation measure which is more robust against outliers.
  +        let bicor seq1 seq2 = 
  +            
  +            let xs,ys  = seq1 |> Array.ofSeq, seq2 |> Array.ofSeq
  +
  +            let xMed = xs |> Array.median
  +            let xMad = xs |> Array.medianAbsoluteDev
  +            let xWeights = xs |> Array.map (bicorHelpers.deviation xMed xMad) |> Array.map bicorHelpers.weight
  +            let xNF = bicorHelpers.getNormalizationFactor xs xWeights xMed
  +
  +            let yMed = ys |> Array.median
  +            let yMad = ys |> Array.medianAbsoluteDev
  +            let yWeights = ys |> Array.map (bicorHelpers.deviation yMed yMad) |> Array.map bicorHelpers.weight
  +            let yNF = bicorHelpers.getNormalizationFactor ys yWeights yMed
  +
  +            bicorHelpers.sumBy4 (fun xVal xWeight yVal yWeight ->
  +                (bicorHelpers.normalize xVal xWeight xNF xMed) * (bicorHelpers.normalize yVal yWeight yNF yMed)
  +                )
  +                xs xWeights ys yWeights 
  +
  +    /// Contains correlation functions optimized for vectors
       [<AutoOpen>]
       module Vector =
   
  
positive.code: namespace FSharp.Stats
  
  module Correlation =
  
      [<AutoOpen>]
      module Seq = 
          /// Pearson correlation 
  
negative.code:         let xCorr lag v1 v2 = 
              correlationOf Vector.dot lag v1 v2
  
      /// Contains correlation functions optimized for matrices
      [<AutoOpen>]
      module Matrix =
      
  