Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/43969
Title: A weighted least-squares cross-validation bandwidth selector for kernel density estimation
Authors: Tenreiro, C. 
Issue Date: 2017
Project: info:eu-repo/grantAgreement/FCT/5876/147205/PT 
Serial title, monograph or event: Communications in Statistics - Theory and Methods
Volume: 46
Issue: 7
Abstract: Since the late 1980s, several methods have been considered in the literature to reduce the sample variability of the least-squares cross-validation bandwidth selector for kernel density estimation. In this article, a weighted version of this classical method is proposed and its asymptotic and finite-sample behavior is studied. The simulation results attest that the weighted cross-validation bandwidth performs quite well, presenting a better finite-sample performance than the standard cross-validation method for “easy-to-estimate” densities, and retaining the good finite-sample performance of the standard cross-validation method for “hard-to-estimate” ones.
URI: http://hdl.handle.net/10316/43969
Other Identifiers: 10.1080/03610926.2015.1062108
Rights: embargoedAccess
Appears in Collections:I&D CMUC - Artigos em Revistas Internacionais

Files in This Item:
File Description SizeFormat
wcvd-author's version.pdf240.75 kBAdobe PDFView/Open
Show full item record

Page view(s)

223
checked on Aug 5, 2020

Download(s)

95
checked on Aug 5, 2020

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.