Bayesian Estimation of Marshall Olkin Extended Inverse Weibull Distribution Using MCMC Approach

被引：1
|
作者：
Hassan M. Okasha
A. H. El-Baz
Abdulkareem M. Basheer
机构：
[1] King AbdulAziz University,Department of Statistics, Faculty of Science
[2] Al-Azhar University,Department of Mathematics, Faculty of Science
[3] Damietta University,Department of Mathematics, Faculty of Science
[4] Al-Bayda University,undefined
来源：
Journal of the Indian Society for Probability and Statistics | 2020年 / 21卷
关键词：
Marshall Olkin extended inverse Weibull; Bayesian estimation; Maximum likelihood estimation; MCMC approach;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we invoke a new prospective to discuss the estimation of a three-parameter Marshall Olkin extended inverse Weibull distribution based on Markov Chain Monte Carlo (MCMC) approach. The Bayes estimators under the squared error loss and LINEX loss functions are derived for three parameters. MCMC approach is applied to compute the Bayesian estimation of the unknown parameters. Using a real data application, it is shown that the superior performance of Bayesian estimation.
引用
收藏
页码：247 / 257
页数：10
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