CARIMA Procedure
Details: CARIMA Procedure
The CARIMA procedure can be used to fit ARIMA models either to time series data or to as transactional data. If the data are transactional, then the procedure must first accumulate the data into a time series before it can forecast them. The procedure uses the sequential steps in Table 2 to produce forecasts, with the options that control the step listed to the right.
Table 2: PROC CARIMA Processing Steps and Control Options
| Step | Operation | Options | Statement |
|---|---|---|---|
| 1 | Accumulation | ACCUMULATE= | ID |
| 2 | Missing value interpretation | SETMISSING= | ID |
| 3 | Parameter estimation | P=, Q= | ESTIMATE |
| 4 | Inverse transformation | TRANSFORM, DIFF | ESTIMATE |
| 5 | Forecasting | LEAD= | FORECAST |
Each of the steps shown in Table 2 is described in the following sections.
Last updated: July 09, 2026