The TIMESERIES Procedure |
PROC TIMESERIES Statement |
The following options can be used in the PROC TIMESERIES statement:
names the SAS data set that contains the input data for the procedure to create the time series. If the DATA= option is not specified, the most recently created SAS data set is used.
specifies the cross-variable graphical output desired. By default, the TIMESERIES procedure produces no graphical output. The following plotting options are available:
plots the time series (OUT= data set).
plots the cross-correlation functions (OUTCROSSCORR= data set).
same as PLOTS=(SERIES CCF).
For example, CROSSPLOTS=SERIES plots the two time series. The CROSSPLOTS= option produces graphical output for these results by using the Output Delivery System (ODS). The CROSSPLOTS= option produces results similar to the data sets listed in parentheses next to the preceding options.
limits the number of warning and error messages that are produced during the execution of the procedure to the specified value. The default is MAXERRORS=50. This option is particularly useful in BY-group processing where it can be used to suppress the recurring messages.
names the output data set to contain the time series variables specified in the subsequent VAR and CROSSVAR statements. If BY variables are specified, they are also included in the OUT= data set. If an ID variable is specified, it is also included in the OUT= data set. The values are accumulated based on the ID statement INTERVAL= or the ACCUMULATE= option or both. The OUT= data set is particularly useful when you want to further analyze, model, or forecast the resulting time series with other SAS/ETS procedures.
names the output data set to contain the univariate time domain statistics.
names the output data set to contain the cross-correlation statistics.
names the output data set to contain the decomposed and/or seasonally adjusted time series.
names the output data set to contain the seasonal statistics. The statistics are computed for each season as specified by the ID statement INTERVAL= option or the PROC TIMESERIES statement SEASONALITY= option. The OUTSEASON= data set is particularly useful when analyzing transactional data for seasonal variations.
names the output data set to contain the univariate frequency domain analysis results.
names the output data set to contain the singular spectrum analysis result series.
names the output data set to contain the descriptive statistics. The descriptive statistics are based on the accumulated time series when the ACCUMULATE= and/or SETMISSING= options are specified in the ID or VAR statements. The OUTSUM= data set is particularly useful when analyzing large numbers of series and a summary of the results are needed.
names the output data set to contain the trend statistics. The statistics are computed for each time period as specified by the ID statement INTERVAL= option. The OUTTREND= data set is particularly useful when analyzing transactional data for trends.
specifies the univariate graphical output desired. By default, the TIMESERIES procedure produces no graphical output. The following plotting options are available:
plots the time series (OUT= data set).
plots the residual time series (OUT= data set).
plots the seasonal cycles (OUT= data set).
plots the correlation panel (OUTCORR= data set).
plots the autocorrelation function (OUTCORR= data set).
plots the partial autocorrelation function (OUTCORR= data set).
plots the inverse autocorrelation function (OUTCORR= data set).
plots the white noise probabilities (OUTCORR= data set).
plots the seasonal adjustment panel (OUTDECOMP= data set).
plots the trend-cycle-seasonal component (OUTDECOMP= data set).
plots the trend-cycle component (OUTDECOMP= data set).
plots the seasonal-irregular component (OUTDECOMP= data set).
plots the seasonal component (OUTDECOMP= data set).
plots the seasonal adjusted component (OUTDECOMP= data set).
plots the percent change in the seasonal adjusted component (OUTDECOMP= data set).
plots the irregular component (OUTDECOMP= data set).
plots the trend component (OUTDECOMP= data set).
plots the cycle component (OUTDECOMP= data set).
plots the periodogram (OUTSPECTRA= data set).
plots the spectral density estimate (OUTSPECTRA= data set).
plots the singular spectrum analysis results (OUTSSA= data set).
same as PLOTS=(SERIES ACF PACF IACF WN SSA).
For example, PLOTS=SERIES plots the time series. The PLOTS= option produces graphical output for these results by using the Output Delivery System (ODS). The PLOTS= option produces results similar to the data sets listed in parentheses next to the preceding options.
specifies the printed output desired. By default, the TIMESERIES procedure produces no printed output. The following printing options are available:
prints the seasonal decomposition/adjustment table (OUTDECOMP= data set).
prints the seasonal statistics table (OUTSEASON= data set).
prints the descriptive statistics for the accumulated time series (OUTSUM= data set).
prints the descriptive statistics table for all time series (OUTSUM= data set).
prints the trend statistics table (OUTTREND= data set).
prints the singular spectrum analysis results (OUTSSA= data set).
same as PRINT=(DESCSTATS SUMMARY).
For example, PRINT=SEASONS prints the seasonal statistics. The PRINT= option produces printed output for these results by using the Output Delivery System (ODS). The PRINT= option produces results similar to the data sets listed in parentheses next to the preceding options.
specifies that output requested with the PRINT= option be printed in greater detail.
specifies the length of the seasonal cycle. For example, SEASONALITY=3 means that every group of three time periods forms a seasonal cycle. By default, the length of the seasonal cycle is one (no seasonality) or the length implied by the INTERVAL= option specified in the ID statement. For example, INTERVAL=MONTH implies that the length of the seasonal cycle is 12.
specifies that the variables specified in the VAR and CROSSVAR statements be processed in sorted order by the variable names. This option allows the output data sets to be presorted by the variable names.
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