Model
is a descriptive label for the model. You can type a label in this field or allow the system to provide a label. If you leave
the label blank, a label is generated automatically based on the p, d, and q terms that you specify. For example, if you specify
p=(1,2,3), d=(1), q=(12)
and no intercept, the model label is ARIMA p=(1,2,3) d=(1) q=(12) NOINT
. For monthly data, this is equivalent to the model ARIMA(3,1,0)(0,0,1)s NOINT
as specified in the ARIMA Model Specification window or the Custom Model Specification window.
ARIMA Options
Specifies the ARIMA model in terms of the autoregressive lags (p), differencing lags (d), and moving-average lags (q).
Autoregressive
defines the autoregressive part of the model. Select the Set button to open the AR Polynomial Specification window, where
you can add any set of autoregressive lags grouped into any number of factors.
Differencing
specifies differencing to be applied to the input data. Select the Set button to open the Differencing Specification window,
where you can specify any set of differencing lags.
Moving Average
defines the moving-average part of the model. Select the Set button to open the MA Polynomial Specification window, where
you can add any set of moving-average lags grouped into any number of factors.
Estimation Method
specifies the method used to estimate the model parameters. The Conditional Least Squares and Unconditional Least Squares
methods generally require fewer computing resources and are more likely to succeed in fitting complex models. The Maximum
Likelihood method requires more resources but provides a better fit in some cases. See also Estimation Details in ChapterĀ 7: The ARIMA Procedure.