OUTMODEL= Data Set
The OUTMODEL= option in the ESTIMATE statement writes
an output data set that enables you to reconstruct the model.
The OUTMODEL= data set contains much the same information as
the OUTEST= data set but in a transposed form that may be more
useful for some purposes.
In addition, the OUTMODEL= data set includes the differencing operators.
The OUTMODEL data set contains the following:
- the BY variables
- _NAME_, a character variable containing the name of the response
or input variable for the observation.
- _TYPE_, a character variable that
contains the estimation method that was employed.
The value of _TYPE_ can be CLS, ULS, or ML.
- [_STATUS_]
This variable describes the convergence status of the model.
A value of 0_CONVERGED indicates that the model converged.
- _PARM_, a character variable containing the name of the parameter
given by the observation.
_PARM_ takes on the values ERRORVAR, MU, AR, MA, NUM, DEN, and DIF.
- _VALUE_, a numeric variable containing the value of the estimate
defined by the _PARM_ variable.
- _STD_, a numeric variable containing the standard error of the estimate.
- _FACTOR_, a numeric variable indicating the number of the factor
to which the parameter belongs.
- _LAG_, a numeric variable containing the number of the term
within the factor containing the parameter.
- _SHIFT_, a numeric variable containing the shift value for the input
variable associated with the current parameter.
The values of _FACTOR_ and _LAG_ identify which particular
MA, AR, NUM, or DEN parameter estimate is given by the _VALUE_ variable.
The _NAME_ variable contains the response variable
name for the MU, AR, or MA parameters.
Otherwise, _NAME_ contains the input variable name associated
with NUM or DEN parameter estimates.
The _NAME_ variable contains the appropriate variable name
associated with the current DIF observation as well.
The _VALUE_ variable is 1 for all DIF observations,
and the _LAG_ variable indicates the degree of differencing employed.
The observations contained in the OUTMODEL= data set are identified
by the _PARM_ variable.
A description of the values of the _PARM_ variable follows:
- NUMRESID
- _VALUE_ contains the number of residuals.
- NPARMS
- _VALUE_ contains the number of parameters in the model.
- NDIFS
- _VALUE_ contains the sum of the differencing lags employed
for the response variable.
- ERRORVAR
- _VALUE_ contains the estimate of the innovation variance.
- MU
- _VALUE_ contains the estimate of the mean term.
- AR
- _VALUE_ contains the estimate of the autoregressive parameter
indexed by the _FACTOR_ and _LAG_ variable values.
- MA
- _VALUE_ contains the estimate of a moving average parameter
indexed by the _FACTOR_ and _LAG_ variable values.
- NUM
- _VALUE_ contains the estimate of the parameter in the numerator factor
of the transfer function of the input variable
indexed by the _FACTOR_, _LAG_, and _SHIFT_ variable values.
- DEN
- _VALUE_ contains the estimate of the parameter in the denominator factor
of the transfer function of the input variable
indexed by the _FACTOR_, _LAG_, and _SHIFT_ variable values.
- DIF
- _VALUE_ contains the difference operator
defined by the difference lag given by the
value in the _LAG_ variable.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
