anchor.diff:      
   let fittingPol = 
       let fit = 
  -        [|1. .. 0.01 .. 10.|] 
  +        [|1. .. 0.1 .. 10.|] 
           |> Array.map (fun x -> x,fittingFunctionPol x)
       Chart.Line(fit)
       |> Chart.withTraceName "order = 3"
   
   let fittingPolW = 
       let fit = 
  -        [|1. .. 0.01 .. 10.|] 
  +        [|1. .. 0.1 .. 10.|] 
           |> Array.map (fun x -> x,fittingFunctionPolW x)
       Chart.Line(fit)
       |> Chart.withTraceName "order = 3 weigthed"
   
  -(*** do-not-eval***)
  -[rawChartP;fittingPol;fittingPolW] 
  -|> Chart.Combine
  -|> Chart.Show
  +let polRegressionChart =
  +    [rawChartP;fittingPol;fittingPolW] 
  +    |> Chart.Combine
  +
  +(*** include-value:polRegressionChart ***)
  +
   
   (**
   ##Nonlinear Regression
  
positive.code: open FSharp.Plotly
  open FSharp.Stats.Fitting.LinearRegression
  
  let x_Data = vector [|1.;2.;3.;|]
  let y_Data = vector [|4.;7.;9.;|]
  
  //Least squares simple linear regression
  let coefficientsLinearLS = 
  
negative.code:     
  let fittingLS = 
      let fit = 
          [|0. .. 11.|] 
          |> Array.map (fun x -> x,fittingFunctionLinearLS x)
      Chart.Line(fit)
      |> Chart.withTraceName "least squares (LS)"
  
  let fittingRobust = 
      let fit = 
          [|0. .. 11.|] 
          |> Array.map (fun x -> x,fittingFunctionLinearRobust x)
      Chart.Line(fit)
      |> Chart.withTraceName "TheilSen estimator"
  
  let fittingRTO = 
      let fit = 
          [|0. .. 11.|] 
          |> Array.map (fun x -> x,fittingFunctionLinearRTO x)
      Chart.Line(fit)
      |> Chart.withTraceName "LS through origin"
  
  let simpleLinearChart =
      [rawChart;fittingLS;fittingRTO;fittingRobust;] 
      |> Chart.Combine
  
  (*** include-value:simpleLinearChart ***)
  
  //Multivariate simple linear regression
  let xVectorMulti =
  