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  • 标题:Bayesian Estimation for Exponentiated Gamma Distribution Under Progressive Type-II Censoring Using Di erent Approximation Techniques
  • 本地全文:下载
  • 作者:Umesh Singh ; Sanjay Kumar Singh ; Abhimanyu Singh Yadav
  • 期刊名称:Journal of Data Science
  • 印刷版ISSN:1680-743X
  • 电子版ISSN:1683-8602
  • 出版年度:2015
  • 卷号:13
  • 期号:3
  • 页码:551-568
  • 出版社:Tingmao Publish Company
  • 摘要:In this paper, we proposed the Bayesian estimation for the parameter and reliability function of exponentiated gamma distribution under progressive type-II censored samples. The Bayes estimate of the parameter and reliability function are derived under the assumption of independent gamma prior by three different approximation methods namely Lindley’s approximation, Tierney-Kadane and Markov Chain Monte Carlo methods. Further, the comparison of Bayes estimators with corresponding maximum likelihood estimators have been carried out through simulation study. Finally, a real data set has been used to illustrate the above study in realistic phenomenon.
  • 关键词:Exponentiated Gamma distribution; Progressive Censoring; Lindley’s approximation; T-K approximation; MCMC technique.
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