IMsArimaTransform.ConfidenceLevel

Syntax

ConfidenceLevel: Double;

Description

The ConfidenceLevel property determines the confidence limits relevance. The property is set to 0.95 by default.

Example

Executing the example requires that the repository contains a modeling container with the KONT_MODEL identifier. The container contains the Var_1 variable, further used as an output one.

Sub Main;

Var

MB: IMetabase;

CrInf: IMetabaseObjectCreateInfo;

MObj: IMetabaseObject;

Model: IMsModel;

Trans: IMsFormulaTransform;

Varr: IMsVariableStub;

VarTrans: IMsFormulaTransformVariable;

Tree: IMsFormulaTransformSlicesTree;

Slice: IMsFormulaTransformSlice;

Selector: IMsFormulaTransformSelector;

Formula: IMsFormula;

ARIMA: IMsArimaTransform;

ARIMASpec: IArimaSpecification;

Begin

MB := MetabaseClass.Active;

CrInf := Mb.CreateCreateInfo;

CrInf.ClassId := MetabaseObjectClass.KE_CLASS_MSMODEL;

CrInf.Id := "New_ARIMA";

CrInf.Name := "New_ARIMA";

CrInf.Parent := Mb.ItemById("KONT_MODEL");

CrInf.Permanent := False;

MObj := Mb.CreateObject(CrInf).Edit;

Model := MObj As IMsModel;

Trans := Model.Transform;

Varr := MB.ItemByIdNamespace("Var_1", MB.ItemById("KONT_MODEL").Key).Bind As IMsVariableStub;

Trans.Outputs.Add(Varr);

VarTrans := Trans.Outputs.Item(0);

Tree := VarTrans.SlicesTree(VarTrans);

Slice := Tree.CreateSlice(1);

Selector := Model.Transform.CreateSelector;

Selector.Slice := Slice;

Formula := Model.Transform.Transform(Selector);

Formula.Kind := MsFormulaKind.Arima;

Formula.Level := DimCalendarLevel.Quarter;

ARIMA := Formula.Method As IMsArimaTransform;

ARIMA.MaxIteration := 100;

ARIMA.ConstantMode := InterceptMode.ManualEstimate;

ARIMA.ConstantValue := 0.03;

//The significance value of confidence limits

ARIMA.ConfidenceLevel := 0.99;

ARIMASpec := ARIMA.ArimaSpecification;

//nonseasonal component

ARIMASpec.AutoRegressionOrder := 1;

ARIMASpec.MovingAverageOrder := 1;

ARIMASpec.DifferenceOrder := 2;

//seasonal component

ARIMASpec.SeasonalAutoRegressionOrder := 1;

ARIMASpec.SeasonalMovingAverageOrder := 2;

ARIMASpec.SeasonalDifferenceOrder := 3;

ARIMASpec.Cycle := 2;

MObj.Save;

End Sub Main;

After executing the example the model that uses the ARIMA method for calculation is created in the modeling container. The output variable is added to the model and seasonal and non-seasonal parameters are set up. The value 0.99 is set for a relevance value of confidence limits.