ON THE BAYESIAN ANALYSIS OF EXTENDED WEIBULL-GEOMETRIC DISTRIBUTION

Pub Date : 2019-11-14 DOI:10.13052/jrss2229-5666.12210
Azeem Ali, Sajid Ali, Shama Khaliq
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引用次数: 2

Abstract

The paper deals with the Bayes estimation of Extended Weibull-Geometric (EWG) distribution. In particular, we discuss Bayes estimators and their posterior risks using the noninformative and informative priors under different loss functions. Since the posterior summaries cannot be obtained analytically, we adopt Markov Chain Monte Carlo (MCMC) technique to assess the performance of Bayes estimates for different sample sizes. A real life example is also part of this study.  
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扩展威布尔几何分布的贝叶斯分析
本文研究了扩展威布尔几何分布的Bayes估计。特别地,我们使用不同损失函数下的非形成性和信息性先验讨论了贝叶斯估计及其后验风险。由于后验摘要无法通过分析获得,我们采用马尔可夫链蒙特卡罗(MCMC)技术来评估不同样本量的贝叶斯估计的性能。一个现实生活中的例子也是这项研究的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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