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The ARIMA Procedure |

PROC ARIMA writes the diagnostic statistics for a model to an output data set when the OUTSTAT= option is specified in the ESTIMATE statement. The OUTSTAT data set contains the following:

- the BY variables.
- _TYPE_, a character variable that contains the estimation method used. _TYPE_ can have the value CLS, ULS, or ML.
- _STAT_, a character variable containing the name of the statistic given by the _VALUE_ variable in this observation. _STAT_ takes on the values AIC, SBC, LOGLIK, SSE, NUMRESID, NPARMS, NDIFS, ERRORVAR, MU, CONV, and NITER.
- _VALUE_, a numeric variable containing the value of the statistic named by the _STAT_ variable.

The observations contained in the OUTSTAT= data set are identified by the _STAT_ variable. A description of the values of the _STAT_ variable follows:

- AIC
- Akaike's information criterion
- SBC
- Schwarz's Bayesian criterion
- LOGLIK
- the log likelihood,
if METHOD=ML or METHOD=ULS is specified
- SSE
- the sum of the squared residuals
- NUMRESID
- the number of residuals
- NPARMS
- the number of parameters in the model
- NDIFS
- the sum of the differencing lags employed for the response variable
- ERRORVAR
- the estimate of the innovation variance
- MU
- the estimate of the mean term
- CONV
- tells if the estimation converged
- NITER
- the number of iterations

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