The X12 Procedure
- Overview
-
Getting Started
-
SyntaxFunctional SummaryPROC X12 StatementADJUST StatementARIMA StatementAUTOMDL StatementBY StatementCHECK StatementESTIMATE StatementEVENT StatementFORECAST StatementID StatementIDENTIFY StatementINPUT StatementOUTLIER StatementOUTPUT StatementPICKMDL StatementREGRESSION StatementSEATSDECOMP StatementTABLES StatementTRANSFORM StatementUSERDEFINED StatementVAR StatementX11 Statement
-
DetailsData RequirementsMissing ValuesSAS Predefined EventsUser-Defined Regression VariablesCombined Test for the Presence of Identifiable SeasonalityComputationsPICKMDL Model SelectionSEATS DecompositionDisplayed Output, ODS Table Names, and OUTPUT Tablename KeywordsUsing Auxiliary Variables to Subset Output Data SetsODS GraphicsOUT= Data SetSEATSDECOMP OUT= Data SetSpecial Data Sets
-
ExamplesARIMA Model IdentificationModel EstimationSeasonal AdjustmentRegARIMA Automatic Model SelectionAutomatic Outlier DetectionUser-Defined RegressorsMDLINFOIN= and MDLINFOOUT= Data SetsSetting Regression ParametersCreating an MDLINFO= Data Set for Use with the PICKMDL StatementIllustration of ODS GraphicsAUXDATA= Data Set
- References
If you are creating an output data set, use the ID statement to copy values of the ID variables, in addition to the table values, into the output data set. Or, if the VAR statement is omitted, all numeric variables that are not identified as BY variables, ID variables, the DATE= variable, or user-defined regressors are processed as time series. The ID statement has no effect when a VAR statement is specified and an output data set is not created. If the DATE= variable is specified in the PROC X12 statement, this variable is included automatically in the OUTPUT data set. If no DATE= variable is specified, the variable _DATE_ is added.
The date variable (or _DATE_ ) values outside the range of the actual data (from forecasting) are extrapolated, while all other ID variables are missing in the forecast horizon.