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dc.contributor.authorAkgül, Fatma Gül
dc.date.accessioned2020-10-05T13:45:17Z
dc.date.available2020-10-05T13:45:17Z
dc.date.issued2019en_US
dc.identifier.citationAkgül, F. G., (2019). Reliability estimation in multicomponentstress–strength model for Topp-Leone distribution, Journal of Statistical Computation and Simulation, 89:15, 2914-2929, DOİ: 10.1080/00949655.2019.1643348.en_US
dc.identifier.urihttps://hdl.handle.net/11494/2289
dc.description.abstractIn this paper, we consider the estimation reliability in multicom-ponent stress-strength (MSS) model when both the stress andstrengths are drawn from Topp-Leone (TL) distribution. The max-imum likelihood (ML) and Bayesian methods are used in the esti-mation procedure. Bayesian estimates are obtained by using Lind-ley’s approximation and Gibbs sampling methods, since they cannotbe obtained in explicit form in the context of TL. The asymptoticconfidence intervals are constructed based on the ML estimators.The Bayesian credible intervals are also constructed using Gibbssampling. The reliability estimates are compared via an extensiveMonte-Carlo simulation study. Finally, a real data set is analysed forillustrative purposes.en_US
dc.language.isoengen_US
dc.publisherTaylor & Francis Incen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMulticomponent stress-strengthen_US
dc.subjectTopp-Leone distributionen_US
dc.subjectML estimationen_US
dc.subjectBayesian estimationen_US
dc.subjectLindley’s approximationen_US
dc.subjectGibbs samplingen_US
dc.subjectMonte-Carlo simulationen_US
dc.titleReliability estimation in multicomponentstress–strength model for Topp-Leone distributionen_US
dc.typearticleen_US
dc.relation.journalJournal of Statistical Computation and Simulationen_US
dc.departmentAÇÜ, Mühendislik Fakültesien_US
dc.identifier.volume89en_US
dc.identifier.issue15en_US
dc.identifier.startpage2914en_US
dc.identifier.endpage2929en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1080/00949655.2019.1643348en_US
dc.contributor.institutionauthorAkgül, Fatma Gülen_US


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