anchor.diff:  
       let normValues (yVal:Vector<float>) =
           let yMean = yVal |> Seq.mean
  -        let std   = yVal |> Seq.stDev
  +        let std   = yVal |> Seq.stDevPopulation
           yVal |> Vector.map (fun x -> (x - yMean) / std) 
          
       type WeightingMethod =
  -        //weight: 1
  +        /// weight: 1
           | Equal
  -        //weight: minmax((1/stDev),Wmin)
  +        /// weight: minmax((1/stDev),Wmin)
           | VarRobust//Variance
  -        //max 0. (log(1./|Seq.cvPopulation g|),2.))
  +        /// max 0. (log(1./|Seq.cvPopulation g|),2.))
           | CV
  -        //weight: (1/stDev)
  +        /// weight: (1/stDev)
           | StandardDeviation
  -        //weight: sqrt(1/stDev)
  +        /// weight: sqrt(1/stDev)
           | StandardDeviationSqrt
  -        //weight: sqrt(1/(stDev/mean))
  +        /// weight: sqrt(1/(stDev/mean))
           | StandardDeviationAdj
  -        //weight: sqrt(sqrt(1/(stDev/mean)))
  +        /// weight: sqrt(sqrt(1/(stDev/mean)))
           | StandardDeviationAdjSqrt
           
       ///creates a weighting matrix out of the x-, and y-Values, the given weighting method and the number of measured replicates.
  
positive.code:         let calcS (h:Vector<float>) (x:Vector<float>) (a:Vector<float>) (c:Vector<float>) (i:int) (t:float) =
              a.[i] * (calcF1 h x i t) + a.[i+1] * (calcF2 h x i t) + c.[i] * (calcF3 h x i t) + c.[i+1] * (calcF4 h x i t)
  
          let evalAt =  calcS h x a c 
      
          (fun t ->
              let i = 
                  match Array.tryFindIndexBack (fun xs -> xs <= t) (x.InternalValues) with 
  
negative.code:             deriv i a.[i .. i+1] c.[i .. i+1] t
              )
  
      [<Obsolete("Only applicable at equal x spacing. Use initEvalTrdDerivativeAt instead")>]    
      ///returns a function that calculates the third derivative for a given xValue
      let getTrdDerivative (x:Vector<float>) (a:Vector<float>) (c:Vector<float>) =
          let n = x.Length
  