Article ID Journal Published Year Pages File Type
6870816 Computational Statistics & Data Analysis 2013 17 Pages PDF
Abstract
Several bandwidth selection procedures for kernel density estimation of a random variable that is sampled under random double truncation are introduced and compared. The motivation is based on the fact that this type of incomplete data is often encountered in astronomy and medicine. The considered bandwidth selection procedures are appropriate modifications of the normal reference rule, the least squares cross-validation procedure, two types of plug-in procedures, and a bootstrap based method. The methods are first shown to work from a theoretical point of view. A simulation study is then carried out to assess the finite sample behavior of these five bandwidth selectors. The use of the various practical bandwidth selectors are illustrated by means of data regarding the luminosity of quasars in astronomy.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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