Estimating composite functions by model selection
Yannick Baraud, Lucien Birgé (2014)
Annales de l'I.H.P. Probabilités et statistiques
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We consider the problem of estimating a function on for large values of by looking for some best approximation of by composite functions of the form . Our solution is based on model selection and leads to a very general approach to solve this problem with respect to many different types of functions and statistical frameworks. In particular, we handle the problems of approximating by additive functions, single and multiple index models, artificial neural networks, mixtures...