On optimal data-based bandwidth selection in kernel density estimation

Hall, Peter; Sheather, Simon J.; Jones, M. C. and Marron, J. S (1991). On optimal data-based bandwidth selection in kernel density estimation. Biometrika, 78(2) pp. 263–269.

DOI (Digital Object Identifier) Link:	http://dx.doi.org/10.1093/biomet/78.2.263
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Abstract

A bandwidth selection method is proposed for kernel density estimation. This is based on the straightforward idea of plugging estimates into the usual asymptotic representation for the optimal bandwidth, but with two important modifications. The result is a bandwidth selector with the, by nonparametric standards, extremely fast asymptotic rate of convergence of n^−½ where n → ∞ denotes sample size. Comparison is given to other bandwidth selection methods, and small sample impact is investigated.

Item Type:	Journal Article
Copyright Holders:	1991 Biometrika Trust
ISSN:	1464-3510
Keywords:	adaptive procedure; convergence rate; functional estimation; mean integrated squared error; smoothing parameter; taylor expansion; window width
Academic Unit/Department:	Mathematics, Computing and Technology > Mathematics and Statistics
Item ID:	28303
Depositing User:	Sarah Frain
Date Deposited:	22 Mar 2011 12:45
Last Modified:	22 Mar 2011 12:45
URI:	http://oro.open.ac.uk/id/eprint/28303
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