Communications in Statistics - Theory and Methods, ( ISI ), Year (2018-12)

Title : ( Nonparametric estimators for quantile density function under length-biased sampling )

Authors: Mahboobe Akbari , Majid Rezaei , Sarah Jomhoori , Vahid Fakoor ,

Citation: BibTeX | EndNote

Abstract

In this article, the strong uniform consistency of two nonparametric estimators for the quantile density function is established under length-biased sampling. The rate of the strong approximation of the resulting processes of these estimators will be presented as well. A Monte Carlo simulation study is carried out to compare the pro- posed estimators with each other in terms of mean squared er

Keywords

, Asymptotic properties; convergence rate; gaussian process; length, biased sampling; quantile density function
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@article{paperid:1071826,
author = {Mahboobe Akbari and Majid Rezaei and Sarah Jomhoori and Fakoor, Vahid},
title = {Nonparametric estimators for quantile density function under length-biased sampling},
journal = {Communications in Statistics - Theory and Methods},
year = {2018},
month = {December},
issn = {0361-0926},
keywords = {Asymptotic properties; convergence rate; gaussian process; length-biased sampling; quantile density function},
}

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%0 Journal Article
%T Nonparametric estimators for quantile density function under length-biased sampling
%A Mahboobe Akbari
%A Majid Rezaei
%A Sarah Jomhoori
%A Fakoor, Vahid
%J Communications in Statistics - Theory and Methods
%@ 0361-0926
%D 2018

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