Regression function estimation as a partly inverse problem - Archive ouverte HAL
Article Dans Une Revue Annals of the Institute of Statistical Mathematics Année : 2020

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.
Fichier principal
Vignette du fichier
Regression.pdf (975.8 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01690856 , version 1 (23-01-2018)
hal-01690856 , version 2 (05-04-2018)
hal-01690856 , version 3 (11-07-2018)
hal-01690856 , version 4 (18-10-2018)

Identifiants

  • HAL Id : hal-01690856 , version 4

Citer

Fabienne Comte, Valentine Genon-Catalot. Regression function estimation as a partly inverse problem. Annals of the Institute of Statistical Mathematics, 2020, 72 (4), pp.1023-1054. ⟨hal-01690856v4⟩
365 Consultations
521 Téléchargements

Partager

More