Details: TIMESERIES Procedure

The TIMESERIES procedure can be used to perform trend and seasonal analysis on transactional data. For trend analysis, various sample statistics are computed for each time period defined by the time ID variable and INTERVAL= option. For seasonal analysis, various sample statistics are computed for each season defined by the INTERVAL= or the SEASONALITY= option. For example, if the transactional data ranges from June 1990 to January 2000 and the data are to be accumulated on a monthly basis, then the trend statistics are computed for every month: June 1990, July 1990, ..., January 2000. The seasonal statistics are computed for each season: January, February, ..., December.

The TIMESERIES procedure can be used to form time series data from transactional data. The accumulated time series can then be analyzed using time series techniques. The data is analyzed in the order described.

1. accumulation

   ACCUMULATE= option

2. missing value interpretation

   SETMISSING= option

3. time series transformation

   TRANSFORM= option

4. time series differencing

   DIF= and SDIF= option

5. descriptive statistics

   OUTSUM= option, PRINT=DESCSTATS

6. seasonal decomposition

   DECOMP statement, OUTDECOMP= option

7. correlation analysis

   CORR statement, OUTCORR= option

8. cross-correlation analysis

   CROSSCORR statement, OUTCROSSCORR= option