Title : ( Some Asymptotic Results of Kernel Density Estimators Under Random Left-Truncation and Dependent Data )
Authors: Vahid Fakoor , Sara Jomhoori ,
Full TextAbstract
Problems with truncated data arise frequently in survival analyses and reliability applications. The estimation of the density function of the lifetimes is often of interest. In this article, the estimation of density function by the kernel method is considered, when truncated data are showing some kind of dependence. We apply the strong Gaussian approximation technique to study the strong uniform consistency for kernel estimators of the density function under a truncated dependent model. We also apply the strong approximation results to study the integrated square error properties of the kernel density estimators under the truncated dependent scheme.
Keywords
Integrated square error; Kiefer process; Strong Gaussian approximation; Strong mixing; Strong uniform consistency; Truncated data.
@article{paperid:1024199,
author = {Fakoor, Vahid and Sara Jomhoori},
title = {Some Asymptotic Results of Kernel Density Estimators Under Random Left-Truncation and Dependent Data},
journal = {Communications in Statistics - Theory and Methods},
year = {2011},
volume = {40},
number = {23},
month = {November},
issn = {0361-0926},
pages = {4249--4262},
numpages = {13},
keywords = {Integrated square error; Kiefer process; Strong Gaussian
approximation; Strong mixing; Strong uniform consistency; Truncated data.},
}
%0 Journal Article
%T Some Asymptotic Results of Kernel Density Estimators Under Random Left-Truncation and Dependent Data
%A Fakoor, Vahid
%A Sara Jomhoori
%J Communications in Statistics - Theory and Methods
%@ 0361-0926
%D 2011
