Geodesic
Statistics
Large deviations theorems in nonparametric regression on functional data
[Théorèmes de grandes déviations pour la régression non paramétrique sur des données fonctionnelles]

Présenté par : Paul Deheuvels

Cherfi, Mohamed1
1 Laboratoire de statistique théorique et appliquée (LSTA), équipe dʼAccueil 3124, université Pierre et Marie Curie – Paris 6, tour 15-25, 2ème étage, 4, place Jussieu, 75252 Paris cedex 05, France
Comptes Rendus. Mathématique, Tome 349 (2011) no. 9-10, pp. 583-585.

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In this Note we prove large deviations principles for the Nadaraya–Watson estimator of the regression of a real-valued variable with a functional covariate. Under suitable conditions, we show pointwise and uniform large deviations theorems.

Lʼobjet de cette Note est dʼétablir un principe de grandes déviations ponctuel et un principe de grandes déviations uniforme pour lʼestimateur à noyau de la régression sur des données fonctionnelles.

Reçu le :
Accepté le :
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DOI : 10.1016/j.crma.2011.04.011

Cherfi, Mohamed 1

1 Laboratoire de statistique théorique et appliquée (LSTA), équipe dʼAccueil 3124, université Pierre et Marie Curie – Paris 6, tour 15-25, 2ème étage, 4, place Jussieu, 75252 Paris cedex 05, France 
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Cherfi, Mohamed. Large deviations theorems in nonparametric regression on functional data. Comptes Rendus. Mathématique, Tome 349 (2011) no. 9-10, pp. 583-585. doi : 10.1016/j.crma.2011.04.011. http://geodesic.mathdoc.fr/articles/10.1016/j.crma.2011.04.011/

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