A weighted least-squares cross-validation bandwidth selector for kernel density estimation (Journal Article)

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Type: Journal Article
National /International: International
Title: A weighted least-squares cross-validation bandwidth selector for kernel density estimation
Publication Date: 2017
Authors: - Carlos Tenreiro
Journal Name: Communications in Statistics - Theory and Methods
Volume: 46
Number: 7
Pages: 3438-3458
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.
Online version: http://www.tandfonli...3610926.2015.1062108
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