Experimenting with Predictors by Applying Saved Models

You've used the Time Series Modeler to create a model for your data and to identify which predictors may prove useful for forecasting. The predictors represent factors that are within your control, so you'd like to experiment with their values in the forecast period to see how forecasts of the dependent variable are affected. This task is easily accomplished with the Apply Time Series Models procedure, using the model file that is created with the Time Series Modeler procedure.

To know more, go to Professional Edition>Forecasting>Experimenting with Predictors by Applying Saved Models

This example is a natural extension of the previous example, , Using the Expert Modeler to Determine Significant Predictors, but this example can also be used independently. The scenario involves a catalog company that has collected data about monthly sales of men's clothing from January 1989 through December 1998, along with several series that are thought to be potentially useful as predictors of future sales. The Expert Modeler has determined that only two of the five candidate predictors are significant: the number of catalogs mailed and the number of phone lines open for ordering.

When planning your sales strategy for the next year, you have limited resources to print catalogs and keep phone lines open for ordering. Your budget for the first three months of 1999 allows for either 2000 additional catalogs or 5 additional phone lines over your initial projections. Which choice will generate more sales revenue for this three-month period?

The data for this example are collected in catalog_seasfac.sav, and catalog_model.xml contains the model of monthly sales that is built with the Expert Modeler. See the topic Sample Files for more information. Of course, if you worked through the previous example and saved your own model file, you can use that file instead of catalog_model.xml.

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