Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/30675
Title: A note on the behaviour of a kernel-smoothed kernel density estimator
Authors: JANSSEN, Paul 
SWANEPOEL, Jan 
VERAVERBEKE, Noel 
Issue Date: 2020
Publisher: ELSEVIER
Source: STATISTICS & PROBABILITY LETTERS, 158 (Art N° 108663)
Abstract: Kernel density estimators have been studied in great detail. In this note a new family of kernels, depending on a parameter c, is obtained by kernel-smoothing an initial kernel density estimator. Under certain conditions, we show that nonparametric density estimators based on such kernels outperform the initial estimator in terms of minimized asymptotic mean integrated squared error and in kernel efficiency.
Notes: Janssen, P (reprint author), Hasselt Univ, Ctr Stat, Agr Laan, B-3590 Diepenbeek, Belgium.
paul.janssen@uhasselt.be; Jan.Swanepoel@nwu.ac.za;
noel.veraverbeke@uhasselt.be
Other: Janssen, P (reprint author), Hasselt Univ, Ctr Stat, Agr Laan, B-3590 Diepenbeek, Belgium. paul.janssen@uhasselt.be; Jan.Swanepoel@nwu.ac.za; noel.veraverbeke@uhasselt.be
Keywords: Asymptotic mean integrated squared error;Kernel density estimator;Kernel efficiency
Document URI: http://hdl.handle.net/1942/30675
ISSN: 0167-7152
e-ISSN: 1879-2103
DOI: 10.1016/j.spl.2019.108663
ISI #: WOS:000509612500023
Rights: 2019 Elsevier B.V. All rights reserved.
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

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