ISmGARCH.CovarianceMatrix

Fore Syntax

CovarianceMatrix: Array;

Fore.NET Syntax

CovarianceMatrix: System.Array;

Description

The CovarianceMatrix property returns covariance matrix values.

Comments

It is required to use an array of Double values.

Fore Example

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

Sub UserProc;
Var
    GARCH: ISmGARCH;
    x: Array[10] Of Double;
    y1, y2: Array[15] Of Double;
    Res, i, j: Integer;
    str: String;
Begin
    GARCH := New SmGARCH.Create;
    // Set values fornbsp;variables
    x[0] := 100; y1[0] := 120; y2[0] := 122;
    x[1] := 111; y1[1] := 125; y2[1] := 127;
    x[2] := 123; y1[2] := 124; y2[2] := 130;
    x[3] := 113; y1[3] := 130; y2[3] := 135;
    x[4] := 119; y1[4] := 133; y2[4] := 140;
    x[5] := 121; y1[5] := Double.Nan; y2[5] := 149;
    x[6] := 125; y1[6] := 139; y2[6] := 150;
    x[7] := 131; y1[7] := 140; y2[7] := 155;
    x[8] := 131; y1[8] := Double.Nan; y2[8] := 155;
    x[9] := 131; y1[9] := 140; y2[9] := Double.Nan;
    y1[10] := 129; y2[10] := 149;
    y1[11] := 139; y2[11] := 150;
    y1[12] := 140; y2[12] := 155;
    y1[13] := 134; y2[13] := 145;
    y1[14] := 140; y2[14] := 165;
    // Set explained variable
    GARCH.Explained.Value := x;
    // Set explanatory variables
    GARCH.Explanatories.Clear;
    GARCH.Explanatories.Add.Value := y1;
    GARCH.Explanatories.Add.Value := y2;
    // Set parameters of the sample and forecast periods
    GARCH.ModelPeriod.FirstPoint := 1;
    GARCH.ModelPeriod.LastPoint := 10;
    // Set forecasting series parameters
    GARCH.Forecast.LastPoint := 15;
    // Set constant determination mode
    GARCH.Intercept.Mode := InterceptMode.AutoEstimate;
     // Set missing data treatment method
    GARCH.MissingData.Method := MissingDataMethod.LinTrend;
    //Use initial values used by default
    GARCH.UseDefaultInitValues := True;
    // Set maximum number of iterations for method calculation
    GARCH.MaxIteration := 100;
    GARCH.Tolerance := 0.0001;
    // Set asymmetry order
    GARCH.AssymetryOrder := 2;
    // Set GARCH model type
    GARCH.GARCHSpec := GARCHSpecType.GARCH;
    // Calculate the method  and output the results
    res := GARCH.Execute;
    If res <> 0 Then
        Debug.WriteLine(GARCH.Errors);
        Else
            Debug.WriteLine("== Covariance coefficients matrix== ");
            For i := 0 To GARCH.CovarianceMatrix.GetUpperBound(1) Do
                str := "";
                For j := 0 To GARCH.CovarianceMatrix.GetUpperBound(2) Do
                    str := str + "  " + (GARCH.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.

Fore.NET Example

The requirements and result of the Fore.NET example execution match with those in the Fore example.

Imports Prognoz.Platform.Interop.Stat;
…
Public Shared Sub Main(Params: StartParams);
Var
    GARCH: ISmGARCH;
    x: Array[10] Of Double;
    y1, y2: Array[15] Of Double;
    Res, i, j: Integer;
    str: String;
    Matrix: System.Array;
Begin
    GARCH := New SmGARCH.Create();
    // Set values fornbsp;variables
    x[0] := 100; y1[0] := 120; y2[0] := 122;
    x[1] := 111; y1[1] := 125; y2[1] := 127;
    x[2] := 123; y1[2] := 124; y2[2] := 130;
    x[3] := 113; y1[3] := 130; y2[3] := 135;
    x[4] := 119; y1[4] := 133; y2[4] := 140;
    x[5] := 121; y1[5] := Double.Nan; y2[5] := 149;
    x[6] := 125; y1[6] := 139; y2[6] := 150;
    x[7] := 131; y1[7] := 140; y2[7] := 155;
    x[8] := 131; y1[8] := Double.Nan; y2[8] := 155;
    x[9] := 131; y1[9] := 140; y2[9] := Double.Nan;
    y1[10] := 129; y2[10] := 149;
    y1[11] := 139; y2[11] := 150;
    y1[12] := 140; y2[12] := 155;
    y1[13] := 134; y2[13] := 145;
    y1[14] := 140; y2[14] := 165;
    // Set explained variable
    GARCH.Explained.Value := x;
    // Set explanatory variables
    GARCH.Explanatories.Clear();
    GARCH.Explanatories.Add().Value := y1;
    GARCH.Explanatories.Add().Value := y2;
    // Set parameters of the sample and forecast periods
    GARCH.ModelPeriod.FirstPoint := 1;
    GARCH.ModelPeriod.LastPoint := 10;
    // Set forecast series parameters
    GARCH.Forecast.LastPoint := 15;
    // Set constant determination mode
    GARCH.Intercept.Mode := InterceptMode.imAutoEstimate;
     // Set missing data treatment method
    GARCH.MissingData.Method := MissingDataMethod.mdmLinTrend;
    //Use initial values used by default
    GARCH.UseDefaultInitValues := True;
    // Set maximum number of iterations for method calculation
    GARCH.MaxIteration := 100;
    GARCH.Tolerance := 0.0001;
    // Set asymmetry order
    GARCH.AssymetryOrder := 2;
    // Set GARCH model type
    GARCH.GARCHSpec := GARCHSpecType.garchstEGARCH;
    // Calculate the method  and output the results
    res := GARCH.Execute();
    If res <> 0 Then
        System.Diagnostics.Debug.WriteLine(GARCH.Errors);
        Else
            System.Diagnostics.Debug.WriteLine("== Covariance coefficients matrix== ");
            Matrix := GARCH.CovarianceMatrix;
            For i := 0 To GARCH.CovarianceMatrix.GetUpperBound(0) Do
                str := "";
                For j := 0 To GARCH.CovarianceMatrix.GetUpperBound(1) Do
                    str := str + "  " + (Matrix[i, j] As Double).ToString();
                End For;
                System.Diagnostics.Debug.WriteLine(str);
            End For;
    End If;
End Sub;