OUTCOV= Data Set
The output data set produced by the OUTCOV= option of the IDENTIFY
statement contains the following variables:
- LAG, a numeric variable containing the lags corresponding to the
values of the covariance variables.
The values of LAG range from 0 to N for covariance functions
and from -N to N for cross-covariance functions,
where N is the value of the NLAG= option.
- VAR, a character variable containing the name of the variable
specified by the VAR= option.
- CROSSVAR, a character variable containing the name of the variable
specified in the CROSSCORR= option, which labels the different
cross-covariance functions.
The CROSSVAR variable is blank for the autocovariance observations.
When there is no CROSSCORR= option, this variable is not created.
- N, a numeric variable containing the number of observations used to
calculate the current value of the covariance or cross-covariance function.
- COV, a numeric variable containing the autocovariance or
cross-covariance function values.
COV contains the autocovariances of the VAR= variable
when the value of the CROSSVAR variable is blank.
Otherwise COV contains the cross covariances
between the VAR= variable and the variable named by the CROSSVAR variable.
- CORR, a numeric variable containing the autocorrelation
or cross-correlation function values.
CORR contains the autocorrelations of the VAR= variable
when the value of the CROSSVAR variable is blank.
Otherwise CORR contains the cross correlations
between the VAR= variable and the variable named by the CROSSVAR variable.
- STDERR, a numeric variable containing the standard errors of the
autocorrelations.
The standard error estimate is based on the
hypothesis that the process generating
the time series is a pure moving-average process of order LAG-1.
For the cross correlations, STDERR contains the value
, which approximates the standard error
under the hypothesis that the two series are uncorrelated.
- INVCORR, a numeric variable containing the inverse autocorrelation
function values of the VAR= variable.
For cross-correlation observations,
(that is, when the value of the CROSSVAR variable is not blank),
INVCORR contains missing values.
- PARTCORR, a numeric variable containing the partial autocorrelation
function values of the VAR= variable.
For cross-correlation observations
(that is, when the value of the CROSSVAR variable is not blank),
PARTCORR contains missing values.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
