Please use this identifier to cite or link to this item:
https://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: | https://hdl.handle.net/10316/43969 | DOI: | 10.1080/03610926.2015.1062108 | Rights: | embargoedAccess |
Appears in Collections: | I&D CMUC - Artigos em Revistas Internacionais |
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wcvd-author's version.pdf | 240.75 kB | Adobe PDF | View/Open |
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