The model evaluation process is described graphically in Figure 52.2.

Model evaluation is based on the one-step-ahead prediction errors for observations within the period of evaluation. The one-step-ahead predictions are generated from the model specification and parameter estimates. The predictions are inverse transformed (median or mean) and adjustments are removed. The prediction errors (the difference of the dependent series and the predictions) are used to compute the statistics of fit, which are described in the section Series Diagnostic Tests. The results generated by the evaluation process are displayed in the Statistics of Fit table of the Model Viewer window.