1403/01/28
اکبر اصغر زاده

اکبر اصغر زاده

مرتبه علمی: استاد
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده علوم ریاضی
نشانی:
تلفن: 011-54302476

مشخصات پژوهش

عنوان
Bayesian prediction of minimal repair times of a series system based on hybrid censored sample of components’ lifetimes under Rayleigh distribution
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Bayesian interval prediction, Bayesian point prediction, coherent systems, highest posterior density, reliability
سال
2017
مجله COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
شناسه DOI
پژوهشگران S.M.T.K. MirMostafaee ، Morteza Amini ، Akbar Asgharzadeh

چکیده

In this paper, we develop Bayesian predictive inferential procedures for prediction of repair times of a series system, applying a minimal repair strategy, using the information contained in an independent observed hybrid censored sample of the lifetimes of the components of the system, assuming the underlying distribution of the lifetimes to be Rayleigh distribution. An illustrative real data example and a simulation study are presented for the purpose of illustration and comparison of the proposed predictors.