IMsPooledModelTransform.ARMA

Syntax

Description

The ARMA property returns autoregression and moving average parameters.

Comments

Be default autoregression order and moving average order are not specified.

Example

Executing the example requires that the repository contains a modeling container with the OBJ_MS identifier. This container must include a model with the MODEL identifier that uses panel data regression method for calculation.

It is also necessary to add links to the Metabase, Ms, Stat system assemblies.

    Sub UserProc;
        Var
        Mb: IMetabase;
        MsDescr: IMetabaseObjectDescriptor;
        Model: IMsModel;
        ModelTransform: IMsFormulaTransform;
        ModelFormula: IMsFormula;
        PooledModel: IMsPooledModelTransform;
        Weights: IMsFormulaTermSet;
        ARMA: ISlARMA;
        OrderAR: Array[2] Of Integer;
    Begin
        Mb := MetabaseClass.Active;
        MsDescr := Mb.ItemById("OBJ_MS");
        Model := MB.ItemByIdNamespace("MODEL", MsDescr.Key).Edit As IMsModel;
        ModelTransform := Model.Transform;
        ModelFormula := ModelTransform.FormulaItem(0);
        PooledModel := ModelFormula.Method As IMsPooledModelTransform;
        PooledModel.CrossSection := PooledModelCrossSectionType.FixedEffect;
        PooledModel.ConstantMode := InterceptMode.ManualEstimate;
        PooledModel.ConstantValue := 0.78;
        PooledModel.ConfidenceLevel := 0.75;
        PooledModel.MissingData.Method := MissingDataMethod.SampleAverage;
        Weights := PooledModel.Weights;
        Weights.Clear;
        ARMA := PooledModel.ARMA;
        OrderAR[0] := 1;
        OrderAR[1] := 3;
        ARMA.OrderAR := OrderAR;
        (Model As IMetabaseObject).Save;
    End Sub UserProc;

After executing the example some parameters of model calculation are changed. The list of changed parameters and its new values:

Model type - model with fixed effects.
Mode of setting constant - value is determined by user.
Constant value - 0.78.
Significance of confidence limits - 0.75.
Missing data treatment method - average.
Weights are not taken place in model calculation.
Autoregression order is specified.

All changes in model calculation parameters are saved.