The 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 following order:
ACCUMULATE= option in the ID, VAR, or CROSSVAR statement
SETMISSING= option in the ID, VAR, or CROSSVAR statement
TRANSFORM= option in the VAR or CROSSVAR statement
DIF= and SDIF= options in the VAR or CROSSVAR statement
OUTSUM= option and the PRINT=DESCSTATS option
DECOMP statement or the OUTDECOMP= option in the PROC TIMESERIES statement
CORR statement or the OUTCORR= option in the PROC TIMESERIES statement
SSA statement or the OUTSSA= option in the PROC TIMESERIES statement
SPECTRA statement or the OUTSPECTRA= option in the PROC TIMESERIES statement
CROSSCORR statement or the OUTCROSSCORR= option in the PROC TIMESERIES statement
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