ISmPhillipsPerronTest.PPStat

Syntax

Description

The PPStat property returns value of the Phillips-Perron test statistics.

Comments

To get the value of adjusted residual variance, use the ISmPhillipsPerronTest.F0 property.

Example

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

Sub UserProc;
Var
    PP: SmPhillipsPerronTest;
    SumStat: ISummaryStatistics;
    PPStat: IUnitRootTestStatistic;
    can: Array[43] Of Double;
    i, res: Integer;
Begin
    PP := New SmPhillipsPerronTest.Create;
    // Set values for variables
    can[0] := 6209; can[1] := 6385; can[2] := 6752; can[3] := Double.Nan; can[4] := 6495;
    can[5] := Double.Nan; can[6] := 7349; can[7] := 7213; can[8] := 7061; can[9] := 7180;
    can[10] := 7132; can[11] := 7137; can[12] := 7473; can[13] := 7722; can[14] := 8088;
    can[15] := 8516; can[16] := 8941; can[17] := 9064; can[18] := 9380; can[19] := 9746;
    can[20] := 9907; can[21] := 10333; can[22] := 10863; can[23] := 11693; can[24] := 12242;
    can[25] := 12227; can[26] := 12910; can[27] := 13049; can[28] := 13384; can[29] := 14036;
    can[30] := 14242; can[31] := 14704; can[32] := 13802; can[33] := 14197; can[34] := 15010;
    can[35] := 15589; can[36] := 15932; can[37] := 16631; can[38] := 17394; can[39] := 17758;
    can[40] := 17308; can[41] := 16444; can[42] := 16413;
    //Select tested series
    PP.Serie.Value := can;
    // Type of tested series
    PP.TestedSeries := ADFTestedSeriesType.Level;
    // Method of missing data treatment
    PP.MissingData.Method := MissingDataMethod.LinTrend;
    // Model type
    PP.Equation := ADFEquationType.Constant;
    // Method of calculation of adjusted residuals variance
    PP.F0SpectrumEstimation := F0SpectrumEstimationType.BartlettKernel;
    // Autoregression order
    PP.AutoRegressionOrder := 9;
    // Sample period
    PP.ModelPeriod.FirstPoint := 1;
    PP.ModelPeriod.LastPoint := 43;
    res := PP.Execute;
    For i := 0 To PP.WarningsCount - 1 Do
        Debug.WriteLine(PP.Warnings[i]);
    End For;
    PPStat := PP.PPStat;
    SumStat := PP.SummaryStatistics;
    If res = 0 Then
        // display statistical values
        Debug.WriteLine("===Phillips-Perron test statistics===");
        Debug.WriteLine("Statistics value: " + PPStat.Statistics.ToString);
        Debug.WriteLine("Probability value: " + PPStat.Probability.ToString);
        Debug.WriteLine("Critical values: ");
        Debug.Indent;
        For i := 0 To PPStat.CriticalValues.Length - 1 Do
            Debug.Write(i.ToString + " ");
            Debug.WriteLine(PPStat.CriticalValues[i]);
        End For;
        Debug.Unindent;
        Debug.WriteLine("Adjusted residuals variance: " + PP.F0.ToString);
        Debug.WriteLine("Residuals variance: " + PP.S0.ToString);
        Debug.WriteLine("===Auxiliary regression===");
        Debug.WriteLine("Auxiliary regression coefficients:");
        Debug.Indent;
        For i := 0 To PP.ModelCoefficients.Estimate.Length - 1 Do
            Debug.WriteLine(PP.ModelCoefficients.Estimate[i]);
        End For;
        Debug.Unindent;
        Debug.WriteLine("Descriptive characteristics of auxiliary regression:");
        Debug.Indent;
        Debug.WriteLine("Fisher statistic: " + SumStat.Fstat.ToString);
        Debug.WriteLine("Probability for Fisher statistics: " + SumStat.ProbFstat.ToString);
        Debug.Unindent;
        Else
            Debug.WriteLine(PP.Errors);
    End If;
End Sub UserProc;

After executing the example the console window displays calculation results for the Phillips-Perron test.