Please use this identifier to cite or link to this item:
Title: Convergence of nonparametric functional regression estimates with functional responses
Authors: Lian, Heng
Issue Date: 2012
Source: Lian, H. (2012). Convergence of nonparametric functional regression estimates with functional responses. Electronic Journal of Statistics, 6(0), 1373-1391.
Series/Report no.: Electronic journal of statistics
Abstract: We consider nonparametric functional regression when both predictors and responses are functions. More specifically, we let (X 1 ,Y 1 ),…,(X n ,Y n ) be random elements in F×H where F is a semi-metric space and H is a separable Hilbert space. Based on a recently introduced notion of weak dependence for functional data, we showed the almost sure convergence rates of both the Nadaraya-Watson estimator and the nearest neighbor estimator, in a unified manner. Several factors, including functional nature of the responses, the assumptions on the functional variables using the Orlicz norm and the desired generality on weakly dependent data, make the theoretical investigations more challenging and interesting.
ISSN: 1935-7524
DOI: 10.1214/12-EJS716
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.