文章基本信息

标题：Quasi-E-Bayesian criteria versus quasi-Bayesian, quasi-hierarchical Bayesian and quasi-empirical Bayesian methods for estimating the scale parameter of the Erlang distribution
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作者：Hesham Reyad ; Adil Younis ; Amal Alkhedir 等
期刊名称：International Journal of Advanced Statistics and Probability
电子版ISSN：2307-9045
出版年度：2016
卷号：4
期号：1
页码：62-74
DOI：10.14419/ijasp.v4i1.6095
出版社：Journal of Advanced Computer Science & Technology
摘要：This paper proposes a new modification for the E-Bayesian method of estimation to introduce a new technique namely Quasi E-Bayesian method (or briefly QE-Bayesian). The suggested criteria built in replacing the likelihood function by the quasi likelihood function in the E-Bayesian technique. This study is devoted to evaluate the performance of the new method versus the quasi-Bayesian, quasi-hierarchical Bayesian and quasi-empirical Bayesian approaches in estimating the scale parameter of the Erlang distribution. All estimators are obtained under symmetric loss function [squared error loss (SELF))] and four different asymmetric loss functions [Precautionary loss function (PLF), entropy loss function (ELF), Degroot loss function (DLF) and quadratic loss function (QLF)]. The properties of the QE-Bayesian estimates are introduced and the relations between the QE-Bayes and quasi-hierarchical Bayes estimates are discussed. Comparisons among all estimators are performed in terms of mean square error (MSE) via Monte Carlo simulation.
关键词：Erlang Distribution;Quasi-Bayes Estimates;Quasi-E-Bayeses Estimates;Quasi-Empirical Bayes Estimates;Quasi-Hierarchical Bayes Esti-mates.