ISmSerialCorrelationLMTest.ChiTest

Fore Syntax

ChiTest: ISpecificationTestStatistic;

Fore.NET Syntax

ChiTest: Prognoz.Platform.Interop.Stat.ISpecificationTestStatistic;

Description

The ChiTest property returns LM-statistics values.

Comments

To get summary statistics, use the ISmSerialCorrelationLMTest.SummaryStatistics property.

Fore Example

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

Sub UserProc;
Var
    Lm: SmSerialCorrelationLMTest;
    d0: Double;
    res: Integer;
    y, y0, y1, y2: Array[9Of Double;
    v: Array Of Double;
    // data output procedure
    Sub Print(Data: Array Of Double);
    Var
        i: Integer;
        CI: ICultureInfo;
    Begin
        CI := CultureInfo.Current;
        Debug.WriteLine("---Begin---");
        For i := 0 To Data.Length - 1 Do
            If Double.IsNan(Data[i]) Then
                Debug.WriteLine("---empty---");
                Else
                    Debug.WriteLine(i.ToString + " " + CI.FormatDoublePrec(Data[i], 4));
            End If;
        End For;
        Debug.WriteLine("---End---");
    End Sub Print;
Begin
    Lm := New SmSerialCorrelationLMTest.Create;
    // values y, y0, y1, y2
    y[0] := 6209; y0[0] := 4110; y1[0] := 3415; y2[0] := 2822;
    y[1] := Double.Nan; y0[1] := 4280; y1[1] := 3673; y2[1] := 3023;
    y[2] := 6752; y0[2] := 4459; y1[2] := 4013; y2[2] := 3131;
    y[3] := 6837; y0[3] := 4545; y1[3] := 4278; y2[3] := 3351;
    y[4] := 6495; y0[4] := 4664; y1[4] := 4577; y2[4] := 3463;
    y[5] := 6907; y0[5] := 4861; y1[5] := 5135; y2[5] := 3686;
    y[6] := 7349; y0[6] := 5195; y1[6] := 5388; y2[6] := 3815;
    y[7] := 7213; y0[7] := 5389; y1[7] := 5610; y2[7] := 3960;
    y[8] := 7061; y0[8] := 5463; y1[8] := 5787; y2[8] := 4119;
    // explained series
    Lm.Explained.Value := y;
    // explanatory series
    Lm.Explanatories.Add.Value := y0;
    Lm.Explanatories.Add.Value := y1;
    Lm.Explanatories.Add.Value := y2;
    // sample period
    Lm.ModelPeriod.FirstPoint := 1;
    Lm.ModelPeriod.LastPoint := 9;
    // Method of missing data treatment
    Lm.MissingData.Method := MissingDataMethod.SampleAverage;
    // Parameters of model coefficients
    Lm.ModelCoefficients.Intercept.Mode := InterceptMode.AutoEstimate;
    // lag
    Lm.LMOrder := 1;
    // test calculation
    res := Lm.Execute;
    If res <> 0 Then
        Debug.WriteLine(Lm.Errors);
        Else
            Debug.WriteLine("=== Fisher Test ===");
            d0 := Lm.FTest.Statistic;
            Debug.WriteLine("Value: " + d0.ToString);
            d0 := Lm.FTest.Probability;
            Debug.WriteLine("Probability: " + d0.ToString);
            Debug.WriteLine("=== LM-statistic ===");
            d0 := Lm.ChiTest.Statistic;
            Debug.WriteLine("Value: " + d0.ToString);
            d0 := Lm.ChiTest.Probability;
            Debug.WriteLine("Probability: " + d0.ToString);
            Debug.WriteLine("== Model coefficients ==");
            v := Lm.ModelCoefficients.Coefficients.Estimate;
            Print(v);
            Debug.WriteLine("== Constant ==");
            d0 := Lm.ModelCoefficients.Intercept.Estimate;
            Debug.WriteLine(d0.ToString);
    End If;
End Sub UserProc;

After executing the example the console window displays results of test calculation:

=== Fisher Test ===

Value: 0.64001648408895

Probability: 0.468521803974844

=== LM-statistic ===

Value: 1.24140687356449

Probability: 0.265200087165467

== Model coefficients ==

---Begin---

0 0,5097

1 0,0356

2 -0,5935

3 -0,4522

---End---

== Constant ==

-521.260748359313

Fore.NET Example

The requirements and result of executing the Fore.NET Example match those of the Fore Example.

Imports Prognoz.Platform.Interop.Stat;

Public Shared Sub Main(Params: StartParams);
Var
    Lm: SmSerialCorrelationLMTest;
    Explanatories: ISlSerie;
    d0: double;
    res: integer;
    y, y0, y1, y2: Array[9Of double;
    v: System.Array;
Begin
    Lm := New SmSerialCorrelationLMTest.Create();
    // values y, y0, y1, y2
    y[0] := 6209; y0[0] := 4110; y1[0] := 3415; y2[0] := 2822;
    y[1] := double.NaN; y0[1] := 4280; y1[1] := 3673; y2[1] := 3023;
    y[2] := 6752; y0[2] := 4459; y1[2] := 4013; y2[2] := 3131;
    y[3] := 6837; y0[3] := 4545; y1[3] := 4278; y2[3] := 3351;
    y[4] := 6495; y0[4] := 4664; y1[4] := 4577; y2[4] := 3463;
    y[5] := 6907; y0[5] := 4861; y1[5] := 5135; y2[5] := 3686;
    y[6] := 7349; y0[6] := 5195; y1[6] := 5388; y2[6] := 3815;
    y[7] := 7213; y0[7] := 5389; y1[7] := 5610; y2[7] := 3960;
    y[8] := 7061; y0[8] := 5463; y1[8] := 5787; y2[8] := 4119;
    // explained series
    Lm.Explained.Value := y;
    // explanatory series
    Explanatories := Lm.Explanatories.Add();
    Explanatories.Value := y0;
    Explanatories.Value := y1;
    Explanatories.Value := y2;
    // sample period
    Lm.ModelPeriod.FirstPoint := 1;
    Lm.ModelPeriod.LastPoint := 9;
    // Method of missing data treatment
    Lm.MissingData.Method := MissingDataMethod.mdmSampleAverage;
    // Parameters of model coefficients
    Lm.ModelCoefficients.Intercept.Mode := InterceptMode.imAutoEstimate;
    // lag
    Lm.LMOrder := 1;
    // test calculation
    res := Lm.Execute();
    If res <> 0 Then
        System.Diagnostics.Debug.WriteLine(Lm.Errors);
        Else
            System.Diagnostics.Debug.WriteLine("=== Fisher Test ===");
            d0 := Lm.FTest.Statistic;
            System.Diagnostics.Debug.WriteLine("Value: " + d0.ToString());
            d0 := Lm.FTest.Probability;
            System.Diagnostics.Debug.WriteLine("Probability: " + d0.ToString());
            System.Diagnostics.Debug.WriteLine("=== LM-statistic ===");
            d0 := Lm.ChiTest.Statistic;
            System.Diagnostics.Debug.WriteLine("Value: " + d0.ToString());
            d0 := Lm.ChiTest.Probability;
            System.Diagnostics.Debug.WriteLine("Probability: " + d0.ToString());
            System.Diagnostics.Debug.WriteLine("== Model coefficients ==");
            v := Lm.ModelCoefficients.Coefficients.Estimate;
            Print(v);
            System.Diagnostics.Debug.WriteLine("== Constant ==");
            d0 := Lm.ModelCoefficients.Intercept.Estimate;
            System.Diagnostics.Debug.WriteLine(d0.ToString());
    End If;
End Sub;

// Data output procedure
Public Shared Sub Print(Data: Array);
Var
    i: Integer;
Begin
    System.Diagnostics.Debug.WriteLine("---Begin---");
    For i := 0 To Data.Length - 1 Do
        If Double.IsNan(Data[i] As  Double) Then
            System.Diagnostics.Debug.WriteLine("---empty---");
            Else
            System.Diagnostics.Debug.WriteLine(i.ToString() + " " + Data[i]);
        End If;
    End For;
    System.Diagnostics.Debug.WriteLine("---End---");
End Sub Print;

See also:

ISmSerialCorrelationLMTest