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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 Type
Dr Grade
Email
زينهم فكري جاهين
Jaheen, Zeinhum F
Researcher
Doctorate
zjaheen@hotmail.com
M M Al Harbi
Al Harbi, M M
Researcher
Doctorate
Files
File Name
Type
Description
33571.pdf
pdf
Abstract
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