ISummaryStatistics.Fstat

Fore Syntax

Fstat: Double;

Fore.NET Syntax

Fstat: double;

Description

The Fstat property returns the Fisher statistics.

Comments

The statistic is used to check the hypothesis on the correlation between a dependent series and regressors.

Fore Example

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

Sub UserProc;
Var
    LinearR: SmLinearRegress;
    can, fr: Array[9] Of Double;
    res, i: Integer;
    Con: IIntercept;
    ss: ISummaryStatistics;
Begin
    LinearR := New SmLinearRegress.Create;
    For i := 0 To 8 Do
        can[i] := 1230 + i * 302;
        fr[i] := 579.5 + i * 9.4;
    End For;
    // Set model parameters
    LinearR.Explained.Value := can;
    LinearR.Explanatories.Add.Value := fr;
    Con := LinearR.ModelCoefficients.Intercept;
    con.Mode := InterceptMode.ManualEstimate;
    con.Estimate := 35.7;
    // Calculate
    res := LinearR.Execute;
    ss := LinearR.SummaryStatistics;
    Debug.Write("Fisher statistic: ");
    Debug.WriteLine(ss.Fstat);
    Debug.Write("Probability for Fisher statistics: ");
    Debug.WriteLine(ss.ProbFstat);
    Debug.Write("Fisher statistic (uncentered): ");
    Debug.WriteLine(ss.Fstat_2);
    Debug.Write("Probability for Fisher statistics (uncentered): ");
    Debug.WriteLine(ss.ProbFstat_2);
End Sub UserProc;

After executing the example the console window displays summary statistics:

Fisher statistics value.
Fisher statistics probability.
Fisher statistics value calculated using uncentered determination coefficient.
Fisher statistics value calculated using uncentered determination coefficient.

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
    LinearR: SmLinearRegress;
    can, fr: Array[9] Of Double;
    res, i: Integer;
    Con: IIntercept;
    ss: ISummaryStatistics;
Begin
    LinearR := New SmLinearRegress.Create();
    For i := 0 To 8 Do
        can[i] := 1230 + i * 302;
        fr[i] := 579.5 + i * 9.4;
    End For;
    // Set model parameters
    LinearR.Explained.Value := can;
    LinearR.Explanatories.Add().Value := fr;
    Con := LinearR.ModelCoefficients.Intercept;
    con.Mode := InterceptMode.imManualEstimate;
    con.Estimate := 35.7;
    // Run calculation
    res := LinearR.Execute();
    ss := LinearR.SummaryStatistics;
    System.Diagnostics.Debug.Write("Fisher statistic: ");
    System.Diagnostics.Debug.WriteLine(ss.Fstat);
    System.Diagnostics.Debug.Write("Probability for Fisher statistics: ");
    System.Diagnostics.Debug.WriteLine(ss.ProbFstat);
    System.Diagnostics.Debug.Write("Fisher statistic (uncentered): ");
    System.Diagnostics.Debug.WriteLine(ss.Fstat_2);
    System.Diagnostics.Debug.Write("Probability for Fisher statistics (uncentered): ");
    System.Diagnostics.Debug.WriteLine(ss.ProbFstat_2);
End Sub;