ISm2SLS.ARMA

Syntax

Description

The ARMA property returns autoregression and moving average parameters.

Comments

By default autoregression order and moving average order are not specified.

Example

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

Sub UserProc;
Var
    TwoSLS: Sm2SLS;
    can, fra, ger: Array[15] Of Double;
    AR, MA: Array[1] Of Integer;
    C: IIntercept;
    MC:ICoefficients;
    ARMA: ISlARMA;
    res, i: Integer;
Begin
    // Create model
    TwoSLS := New Sm2SLS.Create;
    // Set values fornbsp;variables
    can[00] := 6209; fra[00] := 4110; ger[00] := 3415;
    can[01] := 6385; fra[01] := 4280; ger[01] := 3673;
    can[02] := 6752; fra[02] := 4459; ger[02] := 4013;
    can[03] := 6837; fra[03] := 4545; ger[03] := 4278;
    can[04] := 6495; fra[04] := 4664; ger[04] := 4577;
    can[05] := 6907; fra[05] := 4861; ger[05] := 5135;
    can[06] := 7349; fra[06] := 5195; ger[06] := 5388;
    can[07] := 7213; fra[07] := 5389; ger[07] := 5610;
    can[08] := 7061; fra[08] := 5463; ger[08] := 6181;
    can[09] := 7180; fra[09] := 5610; ger[09] := 6181;
    can[10] := 7132; fra[10] := 5948; ger[10] := 6633;
    can[11] := 7180; fra[11] := 6218; ger[11] := 6910;
    can[12] := 7473; fra[12] := 6521; ger[12] := 7146;
    can[13] := 7722; fra[13] := 6788; ger[13] := 7248;
    can[14] := 8088; fra[14] := 7222; ger[14] := 7689;
    // Set sample period parameters
    TwoSLS.ModelPeriod.FirstPoint := 1;
    TwoSLS.ModelPeriod.LastPoint := 15;
    // Use auto estimation of constant value
    C:=TwoSLS.ModelCoefficients.Intercept;
    C.Mode := InterceptMode.AutoEstimate;
    // Set explained variable
    TwoSLS.Explained.Value := can;
    // Set explanatory variables
    TwoSLS.Explanatories.Add.Value := fra;
    TwoSLS.Explanatories.Item(0).Name := "fra";
    // Set instrumental variables
    TwoSLS.Instrumental.Add.Value := ger;
    ARMA := TwoSLS.ARMA;
    AR[0] := 1;
    ARMA.OrderAR := AR;
    MA[0] := 2;
    ARMA.OrderMA := MA;
    // Set maximum number of iterations and solution accuracy
    ARMA.MaxIteration := 30;
    ARMA.Tolerance := 0.5;
    // Use lagged values of explained and explanatory variables
    // as additional tools
    ARMA.UseARMAasInstrums := True;
    // Run calculation and show results
    res := TwoSLS.Execute;
    If res <> 0 Then
        Debug.WriteLine(TwoSLS.Errors);
    Else
        Debug.WriteLine("=== Model coefficients ===");
        Debug.WriteLine("Constant: " + C.Estimate.ToString);
        MC := TwoSLS.ModelCoefficients.Coefficients;
        For i := 0 To MC.Estimate.Length-1 Do
            Debug.WriteLine(TwoSLS.Explanatories.Item(0).Name + ": " + MC.Estimate[i].ToString);
        End For;
        For i := 0 To ARMA.CoefficientsAR.Estimate.Length-1 Do
            Debug.WriteLine("AR(" + AR[i].ToString+"): " + ARMA.CoefficientsAR.Estimate[i].ToString);
        End For;
        For i := 0 To ARMA.CoefficientsMA.Estimate.Length-1 Do
            Debug.WriteLine("MA(" + MA[i].ToString+"): " + ARMA.CoefficientsMA.Estimate[i].ToString);
        End For;
        Debug.WriteLine(" === Descriptive statistics === ");
        Debug.WriteLine("Determination coefficient: " + TwoSLS.SummaryStatistics.R2.ToString);
        Debug.WriteLine("Sum of residuals squares: " + TwoSLS.SummaryStatistics.SSR.ToString);
        Debug.WriteLine("Standard regression error: " + TwoSLS.SummaryStatistics.SE.ToString);
    End If;
End Sub UserProc;

After executing the example the console window displays model coefficients and descriptive statistics.