The TIMESERIES Procedure
- Overview
- Getting Started
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Syntax
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DetailsAccumulationMissing Value InterpretationTime Series TransformationTime Series DifferencingDescriptive StatisticsSeasonal DecompositionCorrelation AnalysisCross-Correlation AnalysisSpectral Density AnalysisSingular Spectrum AnalysisData Set OutputOUT= Data SetOUTCORR= Data SetOUTCROSSCORR= Data SetOUTDECOMP= Data SetOUTPROCINFO= Data SetOUTSEASON= Data SetOUTSPECTRA= Data SetOUTSSA= Data SetOUTSUM= Data SetOUTTREND= Data Set_STATUS_ Variable ValuesPrinted OutputODS Table NamesODS Graphics Names
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Examples
- References
If the ACCUMULATE= option in the ID, VAR, or CROSSVAR statement is specified, data set observations are accumulated within each time period. The frequency (width of each time interval) is specified by the ID statement INTERVAL= option. The ID variable contains the time ID values. Each time ID value corresponds to a specific time period. Accumulation is useful when the input data set contains transactional data, whose observations are not spaced with respect to any particular time interval. The accumulated values form the time series, which is used in subsequent analyses.
For example, suppose a data set contains the following observations:
19MAR1999 10 19MAR1999 30 11MAY1999 50 12MAY1999 20 23MAY1999 20
If the INTERVAL=MONTH is specified, all of the above observations fall within a three-month period of time between March 1999 and May 1999. The observations are accumulated within each time period as follows:
If the ACCUMULATE=NONE option is specified, an error is generated because the ID variable values are not equally spaced with respect to the specified frequency (MONTH).
If the ACCUMULATE=TOTAL option is specified, the resulting time series is:
O1MAR1999 40 O1APR1999 . O1MAY1999 90
If the ACCUMULATE=AVERAGE option is specified, the resulting time series is:
O1MAR1999 20 O1APR1999 . O1MAY1999 30
If the ACCUMULATE=MINIMUM option is specified, the resulting time series is:
O1MAR1999 10 O1APR1999 . O1MAY1999 20
If the ACCUMULATE=MEDIAN option is specified, the resulting time series is:
O1MAR1999 20 01APR1999 . O1MAY1999 20
If the ACCUMULATE=MAXIMUM option is specified, the resulting time series is:
O1MAR1999 30 O1APR1999 . O1MAY1999 50
If the ACCUMULATE=FIRST option is specified, the resulting time series is:
O1MAR1999 10 O1APR1999 . O1MAY1999 50
If the ACCUMULATE=LAST option is specified, the resulting time series is:
O1MAR1999 30 O1APR1999 . O1MAY1999 20
If the ACCUMULATE=STDDEV option is specified, the resulting time series is:
O1MAR1999 14.14 O1APR1999 . O1MAY1999 17.32
As can be seen from the above examples, even though the data set observations contain no missing values, the accumulated time series can have missing values.
When the BOUNDARYALIGN= option is used to qualify the START= or END= options, additional time series values can be incorporated into the accumulation operation. For instance, if a data set contains the following observations
01JAN1999 10 01FEB1999 10 01MAR1999 10 01APR1999 10 01MAY1999 10 01JUN1999 10
and the options START=
01FEB1999d, END=01APR1999d, INTERVAL=QUARTER, and ACCUMULATE=TOTAL are specified, using the BOUNDARYALIGN= option results in the following accumulated
time series:
If BOUNDARYALIGN=START is specified, the accumulated time series is
01JAN1999 30 01APR1999 10
If BOUNDARYALIGN=END is specified, the accumulated time series is
01JAN1999 20 01APR1999 30
If BOUNDARYALIGN=BOTH is specified, the accumulated time series is
01JAN1999 30 01APR1999 30
If BOUNDARYALIGN=NONE is specified, the accumulated time series is
01JAN1999 20 01APR1999 10