Title : ( A Berry-Esseen type bound for the kernel density estimator based on a weakly dependent and randomly left truncated data )
Authors: Petros Asghari , Vahid Fakoor ,
Full TextAbstract
In many applications, the available data come from a sampling scheme that causes loss of information in terms of left truncation. In some cases, in addition to left truncation, the data are weakly dependent. In this paper we are interested in deriving the asymptotic normality as well as a Berry-Esseen type bound for the kernel density estimator of left truncated and weakly dependent data
Keywords
, Keywords: left, truncation; weakly dependent; asymptotic normality; Berry, Esseen; α, mixing
@article{paperid:1060409,
author = {Asghari, Petros and Fakoor, Vahid},
title = {A Berry-Esseen type bound for the kernel density estimator based on a weakly dependent and randomly left truncated data},
journal = {Journal of Inequalities and Applications},
year = {2017},
volume = {2017},
number = {1},
month = {January},
issn = {1029-242X},
pages = {1--19},
numpages = {18},
keywords = {Keywords: left-truncation; weakly dependent; asymptotic normality; Berry-Esseen;
α-mixing},
}
%0 Journal Article
%T A Berry-Esseen type bound for the kernel density estimator based on a weakly dependent and randomly left truncated data
%A Asghari, Petros
%A Fakoor, Vahid
%J Journal of Inequalities and Applications
%@ 1029-242X
%D 2017
