From the Develop Models window, select ** Fit ARIMA Model.** From the ARIMA Model Specification window, select

`Add`

`Regressors`

`Regressors Selection`

For this example, select ** CHEMICAL, Sales: Chemicals and Allied Products**, and

`VEHICLES, Sales: Motor Vehicles and Parts`

`OK`

You must have forecasts of the future values of the regressor variables in order to use them as predictors. To do this, you can specify a forecasting model for each regressor, have the system automatically select forecasting models for the regressors, or supply predicted future values for the regressors in the input data set.

Even if you have supplied future values for a regressor variable, the system requires a forecasting model for the regressor. Future values that you supply in the input data set take precedence over predicted values from the regressor’s forecasting model when the system computes the forecasts for the dependent series.

Select the ** OK** button. The system starts to fit the regression model but then stops and displays a warning that the regressors that you
selected do not have forecasting models, as shown in Figure 50.10.

If you want the system to create forecasting models automatically for the regressor variables by using the automatic model
selection process, select the ** OK** button. If not, you can select the

`Cancel`

For this example, select the ** OK** button. The system now performs the automatic model selection process for CHEMICAL and VEHICLES. The selected forecasting
models for CHEMICAL and VEHICLES are added to the model lists for those series. If you switch the current time series in the
Develop Models window to CHEMICAL or VEHICLES, you will see the model that the system selected for that series.

Once forecasting models have been fit for all regressors, the system proceeds to fit the regression model for PETROL. The fitted regression model is added to the model list displayed in the Develop Models window.