Document Details

Document Type : Article In Journal 
Document Title :
Bayesian estimation for the exponentiated Weibull model via Markov chain Monte Carlo simulation
Bayesian estimation for the exponentiated Weibull model via Markov chain Monte Carlo simulation
 
Subject : Statistics 
Document Language : English 
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. 
ISSN : 0361-0918 
Journal Name : Communications in Statistics - Simulation and Computation 
Volume : 40 
Issue Number : 4 
Publishing Year : 1432 AH
2011 AD 
Article Type : Article 
Added Date : Sunday, June 10, 2012 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
زينهم فكري جاهينJaheen, Zeinhum FResearcherDoctoratezjaheen@hotmail.com
M M Al HarbiAl Harbi, M MResearcherDoctorate 

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