Forecasting with updated data
Given a temporal causal model system, you can generate new forecasts when more current data are available without rebuilding the model system.
- Open the data file tcm_kpi_upd.sav.
This dataset contains the data for four more weeks beyond the data in tcm_kpi.sav. For more information, see the topic Sample Files.
- From the menus, choose:
Figure 1. Apply Temporal Causal Models 
- Browse to the location where you saved the temporal causal model system file and select the file.
- Click the button that is labeled Reestimate models with updated data, create forecasts or generate output describing the temporal causal model system.
- Click Continue.
Figure 2. Temporal Causal Model Forecasting 
- On the Model tab of the Temporal Causal Model
Forecasting dialog, select Reestimate from data, keep the default selection
of All observations, and enter 4 for the value of
Extend records into the future.
Specifying Reestimate from data means that the model parameters are reestimated based on the updated data but that the structure of the models does not change. Specifying All observations ensures that the estimation period includes the four extra time periods in the updated data. Specifying 4 for the value of Extend records into the future generates forecasts for four weeks beyond the end of the estimation period.
- Click the Options tab and then click Output
options in the Select an item list on the Options tab.
Figure 3. Temporal Causal Model Forecasting Output options 
- Deselect all selected items on Output options.
- Click the Save tab.
Figure 4. Temporal Causal Model Forecasting Save 
- Select Predicted Values and keep the default value of Predicted for the root name. Select All targets for Targets to save and enter Predictions for the dataset name.
- Click Run and then select the new Predictions dataset.
