ISmLinearRegress.WeightedSummaryStatistics

Syntax

WeightedSummaryStatistics: ISummaryStatistics;

Description

The WeightedSummaryStatistics property returns weighted descriptive statistics of a model.

Comments

Descriptive statistics are calculated using general formulas. The property does not calculate statistics, not relevant for the current model.

Example

To execute the example, add a link to the Stat system assembly.

Sub UserProc;
Var
    Method: SmLinearRegress;
    can, fra, ger: Array[10] Of Double;
    omega: Array[10, 10] Of Double;
    status, i, j: Integer;
    str: String;
Begin
    Method := New SmLinearRegress.Create;
    // Set explained series
    can[0] := 6209; fra[0] := 4110; ger[0] := 3415;
    can[1] := 6385; fra[1] := 4280; ger[1] := 3673;
    can[2] := 6528; fra[2] := 4459; ger[2] := 4013;
    can[3] := 6837; fra[3] := 4545; ger[3] := 4278;
    can[4] := 6495; fra[4] := 4664; ger[4] := 4577;
    can[5] := 6907; fra[5] := 4861; ger[5] := 5135;
    can[6] := 7349; fra[6] := 5195; ger[6] := 5388;
    can[7] := 7213; fra[7] := 5389; ger[7] := 5610;
    can[8] := 7061; fra[8] := 5463; ger[8] := 5787;
    can[9] := 7180; fra[9] := 5610; ger[9] := 6181;
    For i := 0 To omega.GetUpperBound(1) - 1 Do
        omega[i, i] := 1 + 0.05*i;
    End For;
    // Sample period parameters
    Method.ModelPeriod.FirstPoint := 1;
    Method.ModelPeriod.LastPoint := 10;
    // Choose explained variable
    Method.Explained.Value := can;
    // Choose regressors
    Method.Explanatories.Clear;
    Method.Explanatories.Add.Value := fra;
    Method.Explanatories.Add.Value := ger;
    // Set forecast parameters
    Method.Forecast.LastPoint := 10;
    // Value of weights use
    Method.UseWeights := True;
    // Set covariance matrix for generalized least squares method
    Method.GLSMatrix := omega;
    // Type of weights
    Method.WeightsType := LRWeightsType.StdDeviation;
    // Method of weights scaling
    Method.WeightsScaling := WeightsScalingType.Average;
    //Run calculation and output results
    status := Method.Execute;
    If status <> 0 Then
        Debug.WriteLine(Method.Errors);
    Else
        Debug.WriteLine("=== Summary statistics ===");
        Debug.WriteLine(" Determination coefficient: " + Method.WeightedSummaryStatistics.R2.ToString);
        Debug.WriteLine(" Mean error: " + Method.WeightedSummaryStatistics.ME.ToString);
        Debug.WriteLine(" Standard error: " + Method.WeightedSummaryStatistics.SE.ToString);
        Debug.WriteLine(" Standard deviation of residuals: " + Method.WeightedSummaryStatistics.SEE.ToString);
        Debug.WriteLine("=== Covariance matrix ===");
        For i := 0 To Method.CovarianceMatrix.GetUpperBound(1) Do
            str := "";
            For j := 0 To Method.CovarianceMatrix.GetUpperBound(2) Do
                str := str + "  " + (Method.CovarianceMatrix[i, j] As Double).ToString;
            End For;
            Debug.WriteLine(str);
        End For;
    End If;
End Sub UserProc;

After executing the example the console window displays values of covariance matrix and weighted dscriptive statistics.