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
The OUTCORR= data set contains the variables specified in the BY statement as well as the variables listed below. The OUTCORR= data set records the correlations for each variable specified in a VAR statement (not the CROSSVAR statement).
When the CORR statement TRANSPOSE=NO option is omitted or specified explicitly, the variable names are related to correlation statistics specified in the CORR statement options and the variable values are related to the NLAG= or LAGS= option.
- _NAME_
-
variable name
- LAG
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time lag
- N
-
number of variance products
- ACOV
-
autocovariances
- ACF
-
autocorrelations
- ACFSTD
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autocorrelation standard errors
- ACF2STD
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an indicator of whether autocorrelations are less than (–1), greater than (1), or within (0) two standard errors of zero
- ACFNORM
-
normalized autocorrelations
- ACFPROB
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autocorrelation probabilities
- ACFLPROB
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autocorrelation log probabilities
- PACF
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partial autocorrelations
- PACFSTD
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partial autocorrelation standard errors
- PACF2STD
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an indicator of whether partial autocorrelations are less than (–1), greater than (1), or within (0) two standard errors of zero
- PACFNORM
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partial normalized autocorrelations
- PACFPROB
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partial autocorrelation probabilities
- PACFLPROB
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partial autocorrelation log probabilities
- IACF
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inverse autocorrelations
- IACFSTD
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an indicator of whether inverse autocorrelations are less than (–1), greater than (1), or within (0) two standard errors of zero
- IACF2STD
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two standard errors beyond inverse autocorrelation
- IACFNORM
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normalized inverse autocorrelations
- IACFPROB
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inverse autocorrelation probabilities
- IACFLPROB
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inverse autocorrelation log probabilities
- WN
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white noise test Statistics
- WNPROB
-
white noise test probabilities
- WNLPROB
-
white noise test log probabilities
The preceding correlation statistics are computed for each specified time lag.
When the CORR statement TRANSPOSE=YES option is specified, the variable values are related to correlation statistics specified in the CORR statement and the variable names are related to the NLAG= or LAGS= options.
- _NAME_
-
variable name
- _STAT_
-
correlation statistic name
- _LABEL_
-
correlation statistic label
- LAGh
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correlation statistics for lag h