IMsChowTestSettings.GroupSeparator

Syntax

GroupSeparator: Array;

Description

The GroupSeparator property divides observations of explained series into groups.

Comments

The property is the array that can contain only zeros and ones. Each array element has the observation contained in the sample period of explained series. If the value of array element is zero, the observation is included into the first group; if the element value is one, the observation is included into the second group.

Example

Executing the example requires that the repository contains a modeling container with the CONT_MODEL identifier, which contains a non-linear regression model (OLS estimation) with the MODEL identifier. The model contains more than one factor.

Add links to the Metabase, Ms, Stat system assemblies.

Sub UserProc;
Var
    mb: IMetabase;
    ContModelDescr: IMetabaseObjectDescriptor;
    ModelObj: IMetabaseObject;
    pModel: IMsModel;
    pTransform: IMsFormulaTransform;
    pFormula: IMsFormula;
    pRegress: IMsLinearRegressionTransform;
    pTestList: IMsDiagnosticTestList;
    Test: IMsDiagnosticTest;
    TestSettings: IMsChowTestSettings;
    VarTrans: IMsFormulaTransformVariable;
    Calc: IMsMethodCalculation;
    Coord: IMsFormulaTransformCoord;
    Res: IMsDiagnosticTestResults;
    Stat: IChowTestLinRegress;
    Coef: ICoefficients;
    i: Integer;
    arr: Array Of Integer;
Begin
    mb := MetabaseClass.Active;
    ContModelDescr := mb.ItemById("CONT_MODEL");
    ModelObj := mb.ItemByIdNamespace("MODEL", ContModelDescr.Key).Edit;
    pModel := ModelObj As IMsModel;
    pTransform := pModel.Transform;
    pFormula := pTransform.FormulaItem(0);
    pRegress := pFormula.Method As IMsLinearRegressionTransform;
// get diagnostic tests set
    pTestList := pRegress.DiagnosticTests;
// find Chow tests
    Test := pTestList.FindByType(MsDiagnosticTestType.Chow);
    TestSettings := Test.Settings As IMsChowTestSettings;
// set test type
    TestSettings.TestType := ChowTestType.Forecast;
// set division into groups
    Arr := New Integer[19];
    Arr[0] := 1; Arr[1] := 1; Arr[2] := 1; Arr[3] := 1; Arr[4] := 0;
    Arr[5] := 0; Arr[6] := 0; Arr[7] := 0; Arr[8] := 0; Arr[9] := 0;
    Arr[10] := 0; Arr[11] := 0; Arr[12] := 0; Arr[13] := 0; Arr[14] := 0;
    Arr[15] := 0; Arr[16] := 0; Arr[17] := 0; Arr[18] := 0;
    TestSettings.GroupSeparator := Arr;
// set testing parameters
    VarTrans := pTransform.Outputs.Item(0);
    Coord := pTransform.CreateCoord(VarTrans);
    Calc := pModel.CreateCalculation As IMsMethodCalculation;
    Calc.Period.IdentificationStartDate := DateTime.ComposeDay(1990, 01, 01);
    Calc.Period.IdentificationEndDate := DateTime.ComposeDay(2007, 12, 31);
    Calc.Period.ForecastStartDate := DateTime.ComposeDay(2008, 01, 01);
    Calc.Period.ForecastEndDate := DateTime.ComposeDay(2010, 12, 31);
// execute testing
    Res := Test.Execute(Calc As IMsMethodCalculation, Coord);
// display results
    If Res.FTestResult Then
        Debug.WriteLine("selections are uniform, hypothesis from absence of structure changes accepted");
    Else
        Debug.WriteLine("Selections are not uniform, hypothesis from absence of structure changes is not accepted");
    End If;
    Stat := Res.LR0;
    Coef := Stat.ModelCoefficients.Coefficients;
    Debug.WriteLine("-- Coefficients of first group --");
    For i := 0 To Coef.Estimate.Length - 1 Do
        Debug.WriteLine("   Coefficient " + i.ToString);
        Debug.Write("     Value: ");
        Debug.WriteLine(Coef.Estimate[i]);
        Debug.Write("     Probability: ");
        Debug.WriteLine(Coef.Probability[i]);
    End For;
    Stat := Res.LR1;
    Coef := Stat.ModelCoefficients.Coefficients;
    Debug.WriteLine("-- Coefficients of second group --");
    For i := 0 To Coef.Estimate.Length - 1 Do
        Debug.WriteLine("   Coefficient " + i.ToString);
        Debug.Write("     Value: ");
        Debug.WriteLine(Coef.Estimate[i]);
        Debug.Write("     Probability: ");
        Debug.WriteLine(Coef.Probability[i]);
    End For;
End Sub UserProc;

After executing the example, Chow diagnostic test parameters settings will be determined.

The significance level and test type are determined.
The groups of observations are determined.

The test will be executed, results will be displayed in the console window.