anchor.diff:          /// Compute devMatrix' * devMatrix, the k x k deviation sums of squares and cross products matrix for x.
           let devMTdevM =
               devMatrix.Transpose * devMatrix
  -        /// Step 3: 
  +        /// Step 3:
           /// Then, divide each term in the deviation sums of squares and cross product matrix by n to create the variance-covariance matrix. That is:
           devMTdevM |> map (fun elem -> elem / (float df))
   
  -    /// computes the column specific population covariance matrix of a data matrix 
  +    /// computes the column specific population covariance matrix of a data matrix
       let columnPopulationCovarianceMatrixOf (dataMatrix:Matrix<float>) =
           columnCovarianceMatrixOf dataMatrix.NumRows dataMatrix
   
  
positive.code: 
          member x.Copy () = Matrix.Generic.copy x
  
  
  //    [<AutoOpen>]
  //    module MatrixTopLevelOperators = 
  //
  //        let matrix ll = Matrix.ofSeq ll
  //        let vector l  = Vector.ofSeq  l
  //        let rowvec l  = RowVector.ofSeq l
  
  
negative.code:                 if rowI <> index then
                      for colI=0 to nCols-1 do
                          nm.[nRowI,colI] <- m.[rowI,colI]
                      loop (nRowI-1) (rowI-1)
                  else
                      loop (nRowI) (rowI-1)
  
          loop (nRows-2) (nRows-1)
  
      /// Removes a column at a given index
      let removeColAt index (m:Matrix<_>) =
          let nRows,nCols = m.Dimensions
          //let nm = Matrix.Generic.zero nRows (nCols-1)
          let nm = MG.zeroCreate nRows (nCols-1)
          let rec loop nColI colI =
              if nColI < 0 then
                  nm
  