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  • 标题:Comparison of estimates using censored samples from Gompertz model: Bayesian, E-Bayesian, hierarchical Bayesian and empirical Bayesian schemes
  • 本地全文:下载
  • 作者:Hesham Reyad ; Adil Mousa Younis ; Amal Alsir Alkhedir
  • 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:47-61
  • DOI:10.14419/ijasp.v4i1.5914
  • 出版社:Journal of Advanced Computer Science & Technology
  • 摘要:This paper aims to introduce a comparative study for the E-Bayesian criteria with three various Bayesian approaches; Bayesian, hierarchical Bayesian and empirical Bayesian. This study is concerned to estimate the shape parameter and the hazard function of the Gompertz distribution based on type-II censoring. All estimators are obtained under symmetric loss function [squared error loss (SELF))] and three different asymmetric loss functions [quadratic loss function (QLF), entropy loss function (ELF) and LINEX loss function (LLF)]. Comparisons among all estimators are achieved in terms of mean square error (MSE) via Monte Carlo simulation.
  • 关键词:Bayes estimates;E-Bayes estimates;Empirical Bayes estimates;Gompertz distribution;Hierarchical Bayes estimates.
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