Regression function estimation as a partly inverse problem
Résumé
This paper is about nonparametric regression function estimation. Our estimator is a one step projection estimator obtained by least-squares contrast minimization. The specificity of our work is to consider a new model selection procedure including a cutoff for the underlying matrix inversion, and to provide theoretical risk bounds that apply to non compactly supported bases, a case which was specifically excluded of most previous results. Upper and lower bounds for resulting rates are provided.
Origine | Fichiers produits par l'(les) auteur(s) |
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