The TIMESERIES Procedure
- Overview
- Getting Started
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Syntax
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Details
Accumulation Missing Value Interpretation Time Series Transformation Time Series Differencing Descriptive Statistics Seasonal Decomposition Correlation Analysis Cross-Correlation Analysis Spectral Density Analysis Singular Spectrum Analysis Data Set Output OUT= Data Set OUTCORR= Data Set OUTCROSSCORR= Data Set OUTDECOMP= Data Set OUTPROCINFO= Data Set OUTSEASON= Data Set OUTSPECTRA= Data Set OUTSSA= Data Set OUTSUM= Data Set OUTTREND= Data Set STATUS Variable Values Printed Output ODS Table Names ODS Graphics Names
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Examples
- References
| Missing Value Interpretation |
Sometimes missing values should be interpreted as unknown values. But sometimes missing values are known, such as when missing values are created from accumulation and no observations should be interpreted as no value—that is, zero. In the former case, the SETMISSING= option can be used to interpret how missing values are treated. The SETMISSING=0 option should be used when missing observations are to be treated as no (zero) values. In other cases, missing values should be interpreted as global values, such as minimum or maximum values of the accumulated series. The accumulated and interpreted time series is used in subsequent analyses.