E-Bayesian estimation for the geometric model based on record statistics

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• 作者：Hassan M. Okasha^a ; ^{hassanokasha@yahoo.com" class="auth_mail" title="E-mail the corresponding author} ; Jianhua Wang^b ; ^{wangjh@whut.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：E-Bayesian estimation ; Bayesian estimation ; Geometric distribution ; Upper record statistics values ; Squared error loss function ; Monte Carlo simulation
• 刊名：Applied Mathematical Modelling
• 出版年：2016
• 出版时间：1 January 2016
• 年：2016
• 卷：40
• 期：1
• 页码：658-670
• 全文大小：365 K

文摘

This paper focuses on using a new method (E-Bayesian estimation) for computing estimates of the parameter and reliability function of the geometric distribution. The estimates are derived on the basis of a conjugate prior for the scale parameter. Our computations are based on the balanced loss function, which contains the symmetric and asymmetric loss functions as special cases. The results have been specialized to upper record values. Examples using both real and simulated record values are used to illustrate the application of the results. The results may be of interest in a situation where only record values are stored.