Running the Analysis

To use the Expert Modeler:

  1. From the menus choose:

    Analyze > Forecasting > Create Traditional Models...

    Figure 1. Time Series Modeler dialog box
    Time Series Modeler dialog box
  2. Select Sales of Men's Clothing for the dependent variable.
  3. Select Number of Catalogs Mailed through Number of Customer Service Representatives for the independent variables.
  4. Verify that Expert Modeler is selected in the Method drop-down list. The Expert Modeler will automatically find the best-fitting seasonal or non-seasonal model for the dependent variable series.
  5. Click Criteria and then click the Outliers tab.
    Figure 2. Expert Modeler Criteria dialog box, Outliers tab
    Expert Modeler Criteria dialog box, Outliers tab
  6. Select Detect outliers automatically and leave the default selections for the types of outliers to detect.

    Our visual inspection of the data suggested that there may be outliers. With the current choices, the Expert Modeler will search for the most common outlier types and incorporate any outliers into the final model. Outlier detection can add significantly to the computing time needed by the Expert Modeler, so it is a feature that should be used with some discretion, particularly when modeling many series at once. By default, outliers are not detected.

  7. Click Continue.
  8. Click the Save tab on the Time Series Modeler dialog box.
    Figure 3. Time Series Modeler, Save tab
    Time Series Modeler, Save tab

    You will want to save the estimated model to an external XML file so that you can experiment with different values of the predictors—using the Apply Time Series Models procedure—without having to rebuild the model.

  9. Click the Browse button on the Save tab.

    This will take you to a standard dialog box for saving a file.

  10. Navigate to the folder where you would like to save the XML model file, enter a filename, and click Save.
  11. Click the Statistics tab.
    Figure 4. Time Series Modeler, Statistics tab
    Time Series Modeler, Statistics tab
  12. Select Parameter estimates.

    This option produces a table displaying all of the parameters, including the significant predictors, for the model chosen by the Expert Modeler.

  13. Click the Plots tab.
    Figure 5. Time Series Modeler, Plots tab
    Time Series Modeler, Plots tab
  14. Deselect Forecasts.

    In the current example, we are only interested in determining the significant predictors and building a model. We will not be doing any forecasting.

  15. Select Fit values.

    This option displays the predicted values in the period used to estimate the model. This period is referred to as the estimation period, and it includes all cases in the active dataset for this example. These values provide an indication of how well the model fits the observed values, so they are referred to as fit values. The resulting plot will consist of both the observed values and the fit values.

  16. Click OK in the Time Series Modeler dialog box.

Next