IMsExponentialSmoothingTransform.AsForecasting

Fore Syntax

AsForecasting: Boolean;

Fore.NET Syntax

AsForecasting: boolean;

Description

The AsForecasting property determines whether to calculate forecast values.

Comments

Available values:

True. Method calculates forecast values.
False. Method does not calculate forecast values.

Fore Example

Executing the example requires that the repository contains a modeling container with the MS identifier, containing a model with the MODEL_EXPLSM identifier. This model must be calculated by the Exponential Smoothing method.

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

Sub UserProc;
Var
    MB: IMetabase;
    Model: IMsModel;
    Formula: IMsFormula;
    ExpSmooph: IMsExponentialSmoothingTransform;
    SeasonalComp: ISeasonal;
    Parameters: IExponentialSmoothingParameters;
Begin
    // Get repository
    MB := MetabaseClass.Active;
    // Get model
    Model := (Mb.ItemByIdNamespace("MODEL_EXPLSM", MB.GetObjectKeyById("MS"))).Edit As IMsModel;
    // Get calculation parameters
    Formula := Model.Transform.FormulaItem(0);
    ExpSmooph := Formula.Method As IMsExponentialSmoothingTransform;
    // Set significance of confidence limits
    ExpSmooph.ConfidenceLevel := 0.99;
    // Set missing data treatment method
    ExpSmooph.MissingData.Method := MissingDataMethod.LinTrend;
    // Specify that method calculates forecast values
    ExpSmooph.AsForecasting := True;
    // Set model trend type
    ExpSmooph.TrendComponent := TrendType.Exponential;
    // Set seasonal component parameters
    SeasonalComp := ExpSmooph.SeasonalComponent;
    SeasonalComp.Cycle := 5;
    SeasonalComp.Mode := SeasonalityType.Multiplicative;
    // Set values of method parameters
    Parameters := ExpSmooph.Parameters;
    Parameters.Alpha := 0.06;
    Parameters.Delta := 0.06;
    Parameters.Gamma := 0.01;
    // Save changes
    (Model As IMetabaseObject).Save;
End Sub UserProc;

After executing the example the following is set for the model: confidence limit significance, missing data treatment method, trend type, seasonal component and parameter values. The model calculates forecast values.

Fore.NET Example

The requirements and result of the Fore.NET example execution match with those in the Fore example.

Imports Prognoz.Platform.Interop.Ms;
Imports Prognoz.Platform.Interop.Stat;
…
Public Shared Sub Main(Params: StartParams);
Var
    MB: IMetabase;
    Model: IMsModel;
    Formula: IMsFormula;
    ExpSmooph: IMsExponentialSmoothingTransform;
    SeasonalComp: ISeasonal;
    Parameters: IExponentialSmoothingParameters;
Begin
    // Get repository
    MB := Params.Metabase;
    // Get model
    Model := (Mb.ItemByIdNamespace["MODEL_EXPLSM", MB.GetObjectKeyById("MS")]).Edit() As IMsModel;
    // Get calculation parameters
    Formula := Model.Transform.FormulaItem[0];
    ExpSmooph := Formula.Method As IMsExponentialSmoothingTransform;
    // Set significance of confidence limits
    ExpSmooph.ConfidenceLevel := 0.99;
    // Set missing data treatment method
    ExpSmooph.MissingData.Method := MissingDataMethod.mdmLinTrend;
    // Specify that method calculates forecast values
    ExpSmooph.AsForecasting := True;
    // Set model trend type
    ExpSmooph.TrendComponent := TrendType.tdtExponential;
    // Set seasonal component parameters
    SeasonalComp := ExpSmooph.SeasonalComponent;
    SeasonalComp.Cycle := 5;
    SeasonalComp.Mode := SeasonalityType.sstMultiplicative;
    // Set values of method parameters
    Parameters := ExpSmooph.Parameters;
    Parameters.Alpha := 0.06;
    Parameters.Delta := 0.06;
    Parameters.Gamma := 0.01;
    // Save changes
    (Model As IMetabaseObject).Save();
End Sub;