Model Fit Statistics

The Model Fit table provides fit statistics calculated across all of the models. It provides a concise summary of how well the models, with reestimated parameters, fit the data. For each statistic, the table provides the mean, standard error (SE), minimum, and maximum value across all models. It also contains percentile values that provide information on the distribution of the statistic across models. For each percentile, that percentage of models have a value of the fit statistic below the stated value. For instance, 95% of the models have a value of MaxAPE (maximum absolute percentage error) that is less than 3.676.

While a number of statistics are reported, we will focus on two: MAPE (mean absolute percentage error) and MaxAPE (maximum absolute percentage error). Absolute percentage error is a measure of how much a dependent series varies from its model-predicted level and provides an indication of the uncertainty in your predictions. The mean absolute percentage error varies from a minimum of 0.669% to a maximum of 1.026% across all models. The maximum absolute percentage error varies from 1.742% to 4.373% across all models. So the mean uncertainty in each model's predictions is about 1% and the maximum uncertainty is around 2.5% (the mean value of MaxAPE), with a worst case scenario of about 4%. Whether these values represent an acceptable amount of uncertainty depends on the degree of risk you are willing to accept.

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