Uniform in bandwidth consistency for various kernel estimators involving functional data. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Kara-Zaitri, Lydia; Laksaci, Ali; Rachdi, Mustapha; Vieu, Philippe
• Is Part Of: Journal of nonparametric statistics. Volume 29:Issue 1(2017)
• Page Start: 85
• Page End: 107
• Publication Date: 2017-01-02
• Subjects: Functional data analysis -- uniformity in bandwidth -- small ball probability -- functional regression -- conditional distribution -- conditional density -- conditional hazard function; 62G05 -- 62G08 -- 62G20 -- 62G35 -- 62G07 -- 62G32 -- 62G30 -- Secondary: 62E20; Nonparametric statistics -- Periodicals; 519.5
• DOI: 10.1080/10485252.2016.1254780
• Languages: English
• ISSNs: 1048-5252

Abstract

ABSTRACT: 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.