The X12 Procedure
- Overview
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Getting Started
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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
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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
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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
You can use the SEATSDECOMP statement to output the component series that is computed using the SEATS method of seasonal decomposition.
The OUT= data set specified in the SEATSDECOMP statement contains the BY variables (if any), the ID variables (if any), and
either the DATE= variable if the DATE= option is specified or the variable _DATE_ if the DATE= option is not specified. If user-defined regressor variables or EVENT variables are specified, they are included.
In addition, the five components computed by the SEATS decomposition method are included in the OUT= data set for each series.
The SEATSDECOMP OUT= data set can contain the following variables:
- BY variables
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are the BY variables used to subset the series by BY groups. The BY variables included in this data set match the BY variables (if any) that are used to process the series in the DATA= data set.
- ID variables
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enable the series observations to be identified using further information. The ID variables included in this data set match the ID variables (if any) that are specified in the ID statement and input from the DATA= data set.
- DATE variable
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is the time ID variable used to process the time series. It is either the variable specified in the DATE= option in the PROC X12 statement or the variable
_DATE_that is generated by the START= option in the PROC X12 statement. - _YEAR_ variable
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contains a value for the year of the date variable for the observation. This variable is included in the OUT= data set if YEARSEAS is specified in the OUTPUT statement.
- _SEASON_ variable
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contains a value for the month or quarter of the date variable for the observation. This variable is included in the OUT= data set if YEARSEAS is specified in the OUTPUT statement.
- User-defined variables
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are variables specified in the INPUT statement or the USERVAR= option in the REGRESSION statement. The values of these variables are copied from the DATA= data set or from the AUXDATA= data set.
- EVENT variables
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are variables that are specified in the EVENT statement. The values of these are computed based on the event definition and the dates of the time series observations.
- Component variables
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contains the data from the SEATS decomposition tables. The variable name used in the output data set is the input variable name followed by an underscore and the corresponding table name.
- <
variable>_OS -
contains the original series for SEATS decomposition. This is the B1 series from the X-12-ARIMA method.
- <
variable>_SC -
contains the seasonal component series that is calculated by SEATS decomposition.
- <
variable>_TC -
contains the trend component series that is calculated by SEATS decomposition.
- <
variable>_SA -
contains the seasonally adjusted series that is calculated by SEATS decomposition.
- <
variable>_IC -
contains the irregular series that is calculated by SEATS decomposition.