Article (Scientific journals)
Kernel Selection in Nonparametric Regression
Halconruy, Hélène; Marie, Nicolas
2021In Mathematical Methods of Statistics
Peer reviewed
 

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Keywords :
Kernel selection; Nonparametric regression; PCO method
Abstract :
[en] In the regression model Y=b(X)+ε, where X has a density f, this paper deals with an oracle inequality for an estimator of bf, involving a kernel in the sense of Lerasle et al. (2016), selected via the PCO method. In addition to the bandwidth selection for kernel-based estimators already studied in Lacour, Massart and Rivoirard (2017) and Comte and Marie (2020), the dimension selection for anisotropic projection estimators of f and bf is covered.
Disciplines :
Mathematics
Author, co-author :
Halconruy, Hélène ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH)
Marie, Nicolas;  Université Paris Nanterre > Modal'X > Maître de conférences
External co-authors :
yes
Language :
English
Title :
Kernel Selection in Nonparametric Regression
Publication date :
March 2021
Journal title :
Mathematical Methods of Statistics
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 21 January 2021

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