Indices de sensibilité, sélection de paramètres et erreur quadratique de prédiction : des liaisons dangereuses ?

When a model contains a large number of parameters, sensitivity analysis is often used to select the parameters to be estimated among those identified as the most influent. This selection procedure is based on simulated data and is different from the model validation procedure that is based on real data. Nevertheless, these two processes are interrelated in their objectives and it is interesting to quantify the benefit of this practice in terms of MSEP (Mean