Bandwidth selection for kernel density estimation with length-biased data
Methodology
2017-07-11 v2 Computation
Abstract
Length-biased data are a particular case of weighted data, which arise in many situations: biomedicine, quality control or epidemiology among others. In this paper we study the theoretical properties of kernel density estimation in the context of length-biased data, proposing two consistent bootstrap methods that we use for bandwidth selection. Apart from the bootstrap bandwidth selectors we suggest a rule-of-thumb. These bandwidth selection proposals are compared with a least-squares cross-validation method. A simulation study is accomplished to understand the behaviour of the procedures in finite samples.
Cite
@article{arxiv.1606.05584,
title = {Bandwidth selection for kernel density estimation with length-biased data},
author = {María Isabel Borrajo and Wenceslao González-Manteiga and María Dolores Martínez-Miranda},
journal= {arXiv preprint arXiv:1606.05584},
year = {2017}
}
Comments
35 pages