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The uncertainty in the prediction calculated using the delta method for anoverparameterized (parametric) black-box model is shown to be larger or equalto the uncertainty in the prediction of a canonical (minimal) model. Equalityholds if the additional parameters of the overparameterized model do not addflexibility to the model. As a conclusion, for an overparameterized black-boxmodel, the calculated uncertainty in the prediction by the delta method is notunderestimated. The results are shown analytically and are validated in asimulation experiment where the relationship between the normalized tractionforce and the wheel slip of a car is modelled using e.g., a neural network

On the validity of using the delta method for calculating the uncertainty of the predictions from an overparameterized model