Bayesian Estimation for the Exponentiated Weibull Model via Markov Chain Monte Carlo Simulation |
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Authors: | Zeinhum F. Jaheen Mashail M. Al Harbi |
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Affiliation: | 1. Department of Statistics , King Abdul Aziz University , Jeddah, Saudi Arabia jaheen_64@yahoo.com;3. Department of Mathematics , Applied Science College, Umm Al-Qura University , Saudi Arabia |
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Abstract: | Bayesian estimation for the two unknown parameters and the reliability function of the exponentiated Weibull model are obtained based on generalized order statistics. Markov chain Monte Carlo (MCMC) methods are considered to compute the Bayes estimates of the target parameters. 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 the progressively Type-II censored data and upper record values. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation. |
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Keywords: | Balanced loss function Bayes estimation Exponentiated-Weibull model Generalized order statistics Markov chain Monte Carlo (MCMC) |
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