Document details for 'A modelling approach for bandwidth selection in kernel density estimation'

Authors Brewer, M.J.
Publication details In "COMPSTAT 1998 Proceedings", 203-208. Eds. Payne, R. and Green, P.. Physica-Verlag, Heidelberg.
Publisher details Physica-Verlag, Heidelberg
Keywords Kernel density estimation, Markov chain Monte Carlo, cross-validation

A new procedure is proposed for bandwidth selection in univariate kernel density estimation. Rather than concentrate on minimising some criterion based upon the mean integrated square error (MISE), which depends directly on the (unknown) true density, we build a model for the data and use sampling methods to make inferences about the bandwidths. The model is Bayesian, and it is noted that it allows for systematic adjustment for subjective changes in smoothness of the density estimate.

ISBN 3790811319
Last updated 2015-03-18

Unless explicitly stated otherwise, all material is copyright © Biomathematics and Statistics Scotland.

Biomathematics and Statistics Scotland (BioSS) is formally part of The James Hutton Institute (JHI), a registered Scottish charity No. SC041796 and a company limited by guarantee No. SC374831. Registered Office: JHI, Invergowrie, Dundee, DD2 5DA, Scotland