The X12 Procedure

The X12 procedure can produce more than one table with the same name. For example, the following IDENTIFY statement produces ACF and PACF tables for two levels of differencing:

   identify diff=(1) sdiff=(0, 1);

Auxiliary variables in the output data can be used to subset the data. In this example, the auxiliary variables Diff and SDiff specify the levels of regular and seasonal differencing that are used to compute the ACF. The following statements show how to retrieve the ACF results for the first differenced series:

    ods select acf;
    ods output acf=acf;
    proc x12 data=sashelp.air date=date;
       identify diff=(1) sdiff=(0,1);
    run;
    title "Regular Difference=1 Seasonal Difference=0";
    data acfd1D0;
       set acf(where=(Diff=1 and Sdiff=0));
    run;

In addition to any BY variables, the auxiliary variables in the ACF and PACF data sets are _NAME_, _TYPE_, Transform, Adjust, Regressors, Diff and SDiff. Auxiliary variables can be related to the group as shown in the Results Viewer (for example, BY variables, _NAME_, and _TYPE_). However, they can also be variables in the template where printing is suppressed by using PRINT=OFF. Auxiliary variables such as Transform, Adjust, and Regressors are not displayed in the ACF and PACF tables because similar information is displayed in the ModelDescription table that immediately precedes the ACF and PACF tables. The variables Diff and SDiff are not displayed because the levels of differencing are included in the title of the ACF and PACF tables.

The BY variables and the _NAME_ variable are available for all ODS OUTPUT data sets that are produced by the X12 procedure. The _TYPE_ variable is available for all ODS OUTPUT data sets that are produced during the model identification and model estimation stages. The _TYPE_ variable enables you to determine whether data in a table, such as the ModelDescription table, originated from the model identification stage or the model estimation stage.

The forecast data sets contain the auxiliary variable _SCALE_. The value of _SCALE_ is “Original” or “Transformed” to indicate the scale of the data. The auxiliary variable _SCALE_ is the same as the group in the Results Viewer. It is not displayed in the forecast tables because the table titles indicate the scale of the data.