Journal article

Practical bandwidth selection in deconvolution kernel density estimation

A Delaigle, I Gijbels

COMPUTATIONAL STATISTICS & DATA ANALYSIS | ELSEVIER SCIENCE BV | Published : 2004

Abstract

Kernel estimation of a density based on contaminated data is considered and the important issue of how to choose the bandwidth parameter in practice is discussed. Some plug-in (PI) type of bandwidth selectors, which are based on non-parametric estimation of an approximation of the mean integrated squared error, are proposed. The selectors are a refinement of the simple normal reference bandwidth selector, which is obtained by parametrically estimating the approximated mean integrated squared error by referring to a normal density. A simulation study compares these PI bandwidth selectors with a bootstrap (BT) and a cross-validated (CV) bandwidth selector. It is concluded that in finite sample..

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University of Melbourne Researchers