Title : ( A Berry-Esseen Type Bound for the Kernel Density Estimator of Length-Biased Data )
Authors: Petros Asghari , Vahid Fakoor , Majid Sarmad ,
Full TextAbstract
Length-biased data are widely seen in applications. They are mostly applicable in epidemiological studies or survival analysis in medical researches. Here we aim to propose a Berry-Esseen type bound for the kernel density estimator of this kind of data.The rate of normal convergence in the proposed Berry-Esseen type theorem is shown to be O(n^(-1/6) ) modulo logarithmic term as n tends to infinity by a proper choice of the bandwidth.The results of a simulation study is also presented in this paper inorder to examine the performance of the result.
Keywords
, Asymptotic normality; Berry, Esseen theorem; Kernel estimator; Rate of convergence; Length, biase
@article{paperid:1052455,
author = {Asghari, Petros and Fakoor, Vahid and Sarmad, Majid},
title = {A Berry-Esseen Type Bound for the Kernel Density Estimator of Length-Biased Data},
journal = {Journal of Sciences, Islamic Republic of Iran},
year = {2015},
volume = {26},
number = {3},
month = {July},
issn = {1016-1104},
pages = {265--272},
numpages = {7},
keywords = {Asymptotic normality; Berry-Esseen theorem; Kernel estimator; Rate of convergence;
Length-biase},
}
%0 Journal Article
%T A Berry-Esseen Type Bound for the Kernel Density Estimator of Length-Biased Data
%A Asghari, Petros
%A Fakoor, Vahid
%A Sarmad, Majid
%J Journal of Sciences, Islamic Republic of Iran
%@ 1016-1104
%D 2015
