Document Details

Document Type : Thesis 
Document Title :
Generalized Order Statistics from the Exponentiated Weibull Model and Associated Inference
الإحصاءات المرتبة المعممة من توزيع وايبل الأسي والاستدلال المصاحب
 
Subject : Bayesian Inference 
Document Language : Arabic 
Abstract : The main purpose of the Thesis is to obtain statistical estimation and prediction for the exponentiated Weibull distribution based on generalized order statistics. The Markov chain Monte Carlo (MCMC) method is used for the needed numerical computations. So, The maximum likelihood and Bayes techniques for estimating the parameters, reliability, hazard rate functions and the reliabilities of the stress-strength-models and of the exponentiated Weibull model are made based on generalized order statistics. Also, prediction bounds based on one-sample and two-sample prediction techniques for future generalized order statistic from the exponentiated Weibull model are obtained by using the maximum likelihood and Bayes methods. The symmetric and asymmetric loss functions are used under two types of priors (informative and non-informative) for the two shape parameters of the model. The results are specialized to the progressive type-II censored samples and lower record values. An example of real data is considered. The MCMC technique is used for the computations and the Monte Carlo simulation study is used to compare the different estimates. 
Supervisor : Prof. Dr. Gannat Ramadan AL- Dayian 
Thesis Type : Doctorate Thesis 
Publishing Year : 1432 AH
2011 AD 
Number Of Pages : 237 
Co-Supervisor : Prof. Zeinhum Fekri Jaheen 
Added Date : Wednesday, July 6, 2011 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
مشاعل مسعود الحربيAL HARBI, MASHAIL MASOUDInvestigatorDoctorateMashail1426@gmail.com

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