Jones, M. C.; Marron, J. S. and Sheather, S. J.
|Google Scholar:||Look up in Google Scholar|
There has been major progress in recent years in data-based bandwidth selection for kernel density estimation. Some "second generation" methods, including plug-in and smoothed bootstrap techniques, have been developed that are far superior to well-known "first generation" methods, such as rules of thumb, least squares cross-validation, and biased cross-validation. We recommend a "solve-the-equation" plug-in bandwidth selector as being most reliable in terms of overall performance. This article is intended to provide easy accessibility to the main ideas for nonexperts.
|Item Type:||Journal Article|
|Copyright Holders:||1996 American Statistical Association|
|Keywords:||bandwidth selection; Kernel density estimation; nonparametric curve estimation; smoothing parameter selection|
|Academic Unit/Department:||Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
|Depositing User:||Sarah Frain|
|Date Deposited:||05 May 2011 09:31|
|Last Modified:||15 Jan 2016 15:21|
|Share this page:|