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dc.contributor.authorGürünlü Alma, Özlem
dc.contributor.authorArabi Belaghi, Reza
dc.date.accessioned2020-11-20T17:17:15Z
dc.date.available2020-11-20T17:17:15Z
dc.date.issued2020
dc.identifier.issn2194-6701
dc.identifier.urihttps://doi.org/10.1007/s40304-019-00181-8
dc.identifier.urihttps://hdl.handle.net/20.500.12809/6343
dc.description.abstractComplementary exponential geometric distribution has many applications in survival and reliability analysis. Due to its importance, in this study, we are aiming to estimate the parameters of this model based on progressive type-II censored observations. To do this, we applied the stochastic expectation maximization method and Newton–Raphson techniques for obtaining the maximum likelihood estimates. We also considered the estimation based on Bayesian method using several approximate: MCMC samples, Lindely approximation and Metropolis–Hasting algorithm. In addition, we considered the shrinkage estimators based on Bayesian and maximum likelihood estimators. Then, the HPD intervals for the parameters are constructed based on the posterior samples from the Metropolis–Hasting algorithm. In the sequel, we obtained the performance of different estimators in terms of biases, estimated risks and Pitman closeness via Monte Carlo simulation study. This paper will be ended up with a real data set example for illustration of our purpose. © 2019, School of Mathematical Sciences, University of Science and Technology of China and Springer-Verlag GmbH Germany, part of Springer Nature.en_US
dc.description.sponsorship1059B211600192 Türkiye Bilimsel ve Teknolojik AraÅŸtirma Kurumuen_US
dc.description.sponsorshipThis study was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) and registered in 1059B211600192.en_US
dc.item-language.isoengen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.item-rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBayesian analysisen_US
dc.subjectComplementary exponential geometric (CEG) distributionen_US
dc.subjectMaximum likelihood estimatorsen_US
dc.subjectProgressive type-II censoringen_US
dc.subjectSEM algorithmen_US
dc.subjectShrinkage estimatoren_US
dc.titleEstimation in the Complementary Exponential Geometric Distribution Based on Progressive Type-II Censored Dataen_US
dc.item-typearticleen_US
dc.contributor.departmentMÜ, Fen Fakültesi, İstatistik Bölümüen_US
dc.contributor.institutionauthorGürünlü Alma, Özlem
dc.contributor.institutionauthorArabi Belaghi, Reza
dc.identifier.doi10.1007/s40304-019-00181-8
dc.identifier.volume8en_US
dc.identifier.issue4en_US
dc.identifier.startpage409en_US
dc.identifier.endpage441en_US
dc.relation.journalCommunications in Mathematics and Statisticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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