anchor.diff:  a lower weight to these points as their importance in the shape determination should be decreased.
   
   *)
  -let weightingMethod = TemporalClassification.WeightingMethod.StandardDeviationAdj
  +let weightingMethod = TemporalClassification.Fitting.WeightingMethod.StandardDeviationAdj
   
   //calculate the points weighting according to the specified weightingmethod
  -let weighting = TemporalClassification.getWeighting x_Values y_Values weightingMethod 3
  +let weighting = TemporalClassification.Fitting.getWeighting x_Values y_Values weightingMethod 3
   
   let weightingColumnChart = 
       Matrix.getDiag weighting
  
positive.code:     //defines a function that gives the unconstrained spline value for a given x value
      //the AICc is reported as model selection criterion
      let unconstrainedSpline = 
          TemporalClassification.getInitialEstimateOfWXY weighting means x_Values
          |> fun result -> result.AICc,result.SplineFunction
  
      //defines a function that gives the constrained spline value for a given x value
      //Constraint: One minimum
      //the AICc is reported as model selection criterion
      let monotoneSpline = 
          TemporalClassification.splineIncreasing x_Values means weighting 0
          |> fun (constraintMatrices,result) -> result.AICc,result.SplineFunction
  
      //defines a function that gives the constrained spline value for a given x value
      //Constraint: A maximum, then a minimum
      //the AICc is reported as model selection criterion
      let maxMinSpline = 
          TemporalClassification.splineIncreasing x_Values means weighting 2  
          |> fun (constraintMatrices,result) -> result.AICc,result.SplineFunction
  
      //defines the x_Values, the functions should be fitted with
  
negative.code: let splineChart =
  
      let means = 
          Seq.getMeanOfReplicates 3 y_Values
          |> vector
  
      //plot the means of the replicates as gray dots
      let origPoints = 
  