anchor.diff:          //    let cov = x * x.Transpose
               
           //    cov ./ z
  +
  
positive.code: 
              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 ->
  
negative.code:             m
              |> columnWiseCorrelationMatrix Seq.pearson
  
          /// Computes the rowwise biweighted midcorrelation matrix for the input matrix 
          let rowWiseBicor (m : matrix) =
  
              let vectors = Matrix.toJaggedArray m
              let result : float [] [] = [|for i=0 to vectors.Length-1 do yield (Array.init vectors.Length (fun innerIndex -> if i=innerIndex then 1. else 0.))|]
  
              let meds : float [] = Array.zeroCreate vectors.Length
              let mads : float [] = Array.zeroCreate vectors.Length
              let weightss : float [][] = Array.zeroCreate vectors.Length
              let nfs : float [] = Array.zeroCreate vectors.Length
  
              for i=0 to vectors.Length-1 do
                  let xs = vectors.[i]
                  let xMed = xs |> Array.median
                  let xMad = xs |> Array.medianAbsoluteDev
                  let xWeights = xs |> Array.map ((bicorHelpers.deviation xMed xMad) >> bicorHelpers.weight)
                  let xNF = bicorHelpers.getNormalizationFactor xs xWeights xMed
  
                  meds.[i] <- xMed
                  mads.[i] <- xMad
                  weightss.[i] <- xWeights
                  nfs.[i] <- xNF
  
                  for j=0 to i - 1 do
  
                      let corr = 
                          bicorHelpers.sumBy4 (fun xVal xWeight yVal yWeight ->
                              (bicorHelpers.normalize xVal xWeight xNF xMed) * (bicorHelpers.normalize yVal yWeight nfs.[j] meds.[j]))
                              xs xWeights vectors.[j] weightss.[j]
                      result.[i].[j] <- corr
                      result.[j].[i] <- corr
              result |> matrix
  
          /// Computes the columnwise biweighted midcorrelation matrix for the input matrix 
          let columnWiseBicor (m : matrix) =
              m
              |> Matrix.transpose
              |> rowWiseBicor
  
          ///// Computes rowise pearson correlation
          //// TODO: TEST
          //let corr (x: matrix) =
  