SPSS® 12.0 Command Syntax Reference

160 Syntax Reference
• APPLY with the keyword FIT sets MXITER to 0. If you apply a model that used FIT and
want to obtain estimates, you will need to respecify MXITER.
The keywords available for APPLY with ARIMA are:
SPECIFICATIONS Use only the specifications from the original model. ARIMA should
create the initial values. This is the default.
INITIAL Use the original model’s final estimates as initial values for
estimation.
FIT No estimation. Estimates from the original model should be applied
directly.
Example
ARIMA VAR1
/MODEL=(0,1,1)(0,1,1) 12 LOG NOCONSTANT.
ARIMA APPLY
/MODEL=CONSTANT.
ARIMA VAR2
/APPLY INITIAL.
ARIMA VAR2
/APPLY FIT.
• The first command specifies a model with one degree of differencing, one moving-average
term, one degree of seasonal differencing, and one seasonal moving-average term.
The length of the period is 12. A base 10 log of the series is taken before estimation and
no constant is estimated. This model is assigned the name MOD_1.
• The second command applies the same model to the same series, but this time estimates
a constant term. Everything else stays the same. This model is assigned the name MOD_2.
• The third command uses the same model as the previous command (MOD_2) but applies
it to series VAR2. Keyword INITIAL specifies that the final estimates of MOD_2 are to be
used as the initial values for estimation.
• The last command uses the same model but this time specifies no estimation. Instead, the
values from the previous model are applied directly.
FORECAST Subcommand
The FORECAST subcommand specifies the forecasting method to use. Available methods
are:
EXACT Unconditional least squares. The forecasts are unconditional least squares
forecasts. They are also called finite memory forecasts. This is the default.
CLS Conditional least squares using model constraint for initialization. The forecasts
are computed by assuming that the unobserved past errors are zero and
the unobserved past values of the response series are equal to the mean.
AUTOINIT Conditional least squares using the beginning series values for initialization.
The beginning series values are used to initialize the recursive conditional
least squares forecasting algorithm.