ISmExponentialSmoothing.MissingData

Fore Syntax

Fore.NET Syntax

MissingData: Prognoz.Platform.Interop.Stat.SlMissingData;

Description

The MissingData property determines missing data treatment parameters.

Comments

If the model is estimated with seasonality, the method of missing data treatment is MissingDataMethod.Casewise cannot be used.

Fore Example

Add a link to the Stat system assembly.

Sub UserProc;
Var
    Method: SmExponentialSmoothing;
    serie: Array[15] Of Double;
    Seasonal: ISeasonal;
    status, i: Integer;
Begin
    Method := New SmExponentialSmoothing.Create;
    serie[0] := 670.2000183;  serie[1] := 576.0680563;  serie[2] := Double.Nan;
    serie[3] := 856.9105808;  serie[4] := 885.4609516;  serie[5] := 1011.846431;
    serie[6] := 995.4496292;  serie[7] := 1064.74221;   serie[8] := Double.Nan;
    serie[9] := 717.6484268;  serie[10] := 751.9611194; serie[11] := 654.5472579;
    serie[12] := 678.2380139; serie[13] := 642.4128544; serie[14] := Double.Nan;
    Method.Serie.Value := serie;
    Method.Forecast.LastPoint := 40;
    Method.MissingData.Method := MissingDataMethod.LinInterpolation;
    Seasonal := Method.SeasonalComponent;
    Seasonal.Mode := SeasonalityType.Additive;
    Seasonal.Cycle := 4;
    status := Method.Execute;
    If status <> 0 Then
        Debug.WriteLine(Method.Errors);
        Else
            Debug.WriteLine("=== Model series ===");
            Debug.Indent;
            For i := 0 To Method.Fitted.Length - 1 Do
                Debug.WriteLine(Method.Fitted[i]);
            End For;
            Debug.Unindent;
    End If;
End Sub UserProc;

After executing the example the console window displays the modeling series.

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
    Method: SmExponentialSmoothing;
    serie: Array[15] Of Double;
    Seasonal: ISeasonal;
    status, i: Integer;
    Fitted: System.Array;
Begin
    Method := New SmExponentialSmoothing.Create();
    serie[0] := 670.2000183;  serie[1] := 576.0680563;  serie[2] := Double.Nan;
    serie[3] := 856.9105808;  serie[4] := 885.4609516;  serie[5] := 1011.846431;
    serie[6] := 995.4496292;  serie[7] := 1064.74221;   serie[8] := Double.Nan;
    serie[9] := 717.6484268;  serie[10] := 751.9611194; serie[11] := 654.5472579;
    serie[12] := 678.2380139; serie[13] := 642.4128544; serie[14] := Double.Nan;
    Method.Serie.Value := serie;
    Method.Forecast.LastPoint := 40;
    Method.MissingData.Method := MissingDataMethod.mdmLinInterpolation;
    Seasonal := Method.SeasonalComponent;
    Seasonal.Mode := SeasonalityType.sstAdditive;
    Seasonal.Cycle := 4;
    status := Method.Execute();
    If status <> 0 Then
        System.Diagnostics.Debug.WriteLine(Method.Errors);
        Else
            System.Diagnostics.Debug.WriteLine("=== Model series ===");
            System.Diagnostics.Debug.Indent();
            Fitted := Method.Fitted;
            For i := 0 To Method.Fitted.Length - 1 Do
                System.Diagnostics.Debug.WriteLine(Fitted[i]);
            End For;
            System.Diagnostics.Debug.Unindent();
    End If;
End Sub;