Classical and Bayesian estimation of multicomponent stress–strength reliability for exponentiated Pareto distribution
Yükleniyor...
Dosyalar
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study deals with the classical and Bayesian estimation of reliability in a multicomponent stress–strength model by assuming that both stress and strength variables follow exponentiated Pareto distribution. First, the maximum likelihood method is used to estimate reliability. The asymptotic confidence interval is constructed. We also propose two bootstrap confidence intervals. Next, the Bayesian estimates of reliability are obtained using Lindley’s approximation, Tierney–Kadane approximation and the Markov chain Monte Carlo (MCMC) method since there are no explicit forms. The MCMC method is used to construct the Bayesian credible interval. A Monte Carlo simulation study is performed to compare the performance of the corresponding methods. Finally, the hydrological data set is analyzed in the application part.
Açıklama
Anahtar Kelimeler
Multicomponent stress–strength model, Exponentiated pareto distribution, Maximum likelihood estimation, Bayesian estimation, Monte Carlo simulation
Kaynak
Soft Computing
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
25
Sayı
14
Künye
Akgül, F. G. (2021). Classical and Bayesian estimation of multicomponent stress–strength reliability for exponentiated Pareto distribution. Soft Computing, 25(14), 9185-9197.
