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A reliable data-based bandwidth selection method for kernel density estimation

Sheather, S.J. and Jones, Chris (1991). A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 53(3) pp. 683–690.

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Abstract

We present a new method for data-based selection of the bandwidth in kernel density estimation which has excellent properties. It improves on a recent procedure of Park and Marron (which itself is a good method) in various ways. First, the new method has superior theoretical performance; second, it also has a computational advantage; third, the new method has reliably good performance for smooth densities in simulations, performance that is second to none in the existing literature. These methods are based on choosing the bandwidth to (approximately) minimize good quality estimates of the mean integrated squared error. The key to the success of the current procedure is the reintroduction of a non- stochastic term which was previously omitted together with use of the bandwidth to reduce bias in estimation without inflating variance.

Item Type: Journal Article
Copyright Holders: 1991 Royal Statistical Society
ISSN: 1467-9868
Keywords: adaptive choice; bias reduction; functional estimation; smoothing; squared error loss functions
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 28316
Depositing User: Sarah Frain
Date Deposited: 17 Mar 2011 11:50
Last Modified: 17 Mar 2011 11:50
URI: http://oro.open.ac.uk/id/eprint/28316
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