Options
The Options tab allows you to set the forecast period, specify the handling of missing values, set the confidence interval width, specify a custom prefix for model identifiers, and set the number of lags shown for autocorrelations.
Forecast Period. The forecast period always begins with the first case after the end of the estimation period (the set of cases used to determine the model) and goes through either the last case in the active dataset or a user-specified date. By default, the end of the estimation period is the last case in the active dataset, but it can be changed from the Select Cases dialog box by selecting Based on time or case range.
- First case after end of estimation period through last case in active dataset. Select this option when the end of the estimation period is prior to the last case in the active dataset, and you want forecasts through the last case. This option is typically used to produce forecasts for a holdout period, allowing comparison of the model predictions with a subset of the actual values.
-
First case after end
of estimation period through a specified date. Select
this option to explicitly specify the end of the forecast period.
This option is typically used to produce forecasts beyond the end
of the actual series. Enter values for all of the cells in the Date
grid.
If no date specification has been defined for the active dataset, the Date grid shows the single column Observation. To specify the end of the forecast period, enter the row number (as displayed in the Data Editor) of the relevant case.
The Cycle column (if present) in the Date grid refers to the value of the CYCLE_ variable in the active dataset.
User-Missing Values. These options control the handling of user-missing values.
- Treat as invalid. User-missing values are treated like system-missing values.
- Treat as valid. User-missing values are treated as valid data.
Missing Value Policy. The following rules apply to the treatment of missing values (includes system-missing values and user-missing values treated as invalid) during the modeling procedure:
- Cases with missing values of a dependent variable that occur within the estimation period are included in the model. The specific handling of the missing value depends on the estimation method.
- A warning is issued if an independent variable has missing values within the estimation period. For the Expert Modeler, models involving the independent variable are estimated without the variable. For custom ARIMA, models involving the independent variable are not estimated.
- If any independent variable has missing values within the forecast period, the procedure issues a warning and forecasts as far as it can.
Confidence Interval Width (%). Confidence intervals are computed for the model predictions and residual autocorrelations. You can specify any positive value less than 100. By default, a 95% confidence interval is used.
Prefix for Model Identifiers in Output. Each dependent variable specified on the Variables tab gives rise to a separate estimated model. Models are distinguished with unique names consisting of a customizable prefix along with an integer suffix. You can enter a prefix or leave the default of Model.
Maximum Number of Lags Shown in ACF and PACF Output. You can set the maximum number of lags shown in tables and plots of autocorrelations and partial autocorrelations.
To Set Options, Including the Forecast Period, Missing Values, and Confidence Intervals
This feature requires the Forecasting option.
- From the menus choose:
- Click the Options tab.