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Uniform in bandwidth consistency for various kernel estimators involving functional data
Journal article   Peer reviewed

Uniform in bandwidth consistency for various kernel estimators involving functional data

Lydia Kara-Zaitri, Ali Laksaci, Mustapha Rachdi and Philippe Vieu
Journal of nonparametric statistics, Vol.29(1), pp.85-107
02/01/2017
DOI: https://doi.org/10.1080/10485252.2016.1254780

Abstract

conditional density conditional distribution conditional hazard function Functional data analysis functional regression Secondary: 62E20 small ball probability uniformity in bandwidth
The paper investigates various nonparametric models including regression, conditional distribution, conditional density and conditional hazard function, when the covariates are infinite dimensional. The main contribution is to prove uniform in bandwidth asymptotic results for kernel estimators of these functional operators. Then, the application issues, involving data-driven bandwidth selection, are discussed.

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