The TIMESERIES Procedure
- Overview
- Getting Started
-
Syntax
-
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
| OUTCORR= Data Set |
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
time lag
- N
number of variance products
- ACOV
autocovariances
- ACF
autocorrelations
- ACFSTD
autocorrelation standard errors
- ACF2STD
an indicator of whether autocorrelations are less than (–1), greater than (1), or within (0) two standard errors of zero
- ACFNORM
normalized autocorrelations
- ACFPROB
autocorrelation probabilities
- ACFLPROB
autocorrelation log probabilities
- PACF
partial autocorrelations
- PACFSTD
partial autocorrelation standard errors
- PACF2STD
an indicator of whether partial autocorrelations are less than (–1), greater than (1), or within (0) two standard errors of zero
- PACFNORM
partial normalized autocorrelations
- PACFPROB
partial autocorrelation probabilities
- PACFLPROB
partial autocorrelation log probabilities
- IACF
inverse autocorrelations
- IACFSTD
an indicator of whether inverse autocorrelations are less than (–1), greater than (1), or within (0) two standard errors of zero
- IACF2STD
two standard errors beyond inverse autocorrelation
- IACFNORM
normalized inverse autocorrelations
- IACFPROB
inverse autocorrelation probabilities
- IACFLPROB
inverse autocorrelation log probabilities
- WN
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
correlation statistics for lag h