var1,var2,var3
0.942856823,0.568425866,0.325885379
1.227681099,1.335672206,0.925331054
1.952671045,1.829479996,1.512280854
2.45428731,1.990174152,1.534456808
2.987783477,2.78975186,1.725095748
3.651682331,2.966399127,1.972274564
3.768010479,3.211381506,1.993080807
4.509429614,3.642983433,2.541071547
4.81498729,3.888415006,3.218031802

open System.IO
open MathNet.Numerics.LinearAlgebra
let rows = [|for line in File.ReadAllLines("Z:\mypath.csv")
            |> Seq.skip 1 do yield line.Split(',') |> Array.map float|]
let data = DenseMatrix.ofRowArrays rows

let data_logdiff =
    DenseMatrix.init (data.RowCount-1) (data.ColumnCount)
        (fun j i -> if j = 0 then 0. else data.At(j, i) / data.At(j-1, i) |> log)

let alpha = vector [for i in data_logdiff.EnumerateColumns() -> i |> Statistics.Mean]

let sigsq (values:Vector<float>) (avg: float) =
    let sqr x = x * x
    let result = values |> (fun i -> sqr (i - avg))
    result

sigsq (data_logdiff.Column(i), alpha.[0]) |> printfn "%A"

let sigsq (values:Vector<float>) (avg: float) =

sigsq (data_logdiff.Column(i), alpha.[0]) |> printfn "%A"

sigsq (data_logdiff.Column(0)) (alpha.[0])

sigsq <| data_logdiff.Column(0) <| alpha.[0]

data_logdiff.Column(0) |> sigsq <| alpha.[0]