Estimation in Weibull Distribution Under Progressively Typ e-I Hybrid Censored Data

Basit Öğe Kaydı
dc.contributor.authorAsar, Yasin
dc.contributor.authorBelaghi, Reza Arabi
dc.date.accessioned2024-02-23T14:44:43Z
dc.date.available2024-02-23T14:44:43Z
dc.date.issued2022
dc.departmentNEÜen_US
dc.description.abstractIn this article, we consider the estimation of unknown parameters of Weibull distribution when the lifetime data are observed in the presence of progressively typ e-I hybrid censoring scheme. The Newton-Raphson algorithm, Expectation-Maximization (EM) algorithm and Stochastic EM algorithm are utilized to derive the maximum likelihood estimates for the unknown parameters. Moreover, Bayesian estimators using Tierney-Kadane Method and Markov Chain Monte Carlo method are obtained under three different loss functions, namely, squared error loss, linear-exponential and generalized entropy loss functions. Also, the shrinkage pre-test estimators are derived. An extensive Monte Carlo simulation experiment is conducted under different schemes so that the performances of the listed estimators are compared using mean squared error, confidence interval length and coverage probabilities. Asymptotic normality and MCMC samples are used to obtain the confidence intervals and highest posterior density intervals respectively. Further, a real data example is presented to illustrate the methods. Finally, some conclusive remarks are presented.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK); BIDEB-2219 Postdoctoral Research Program [1059B191700537]en_US
dc.description.sponsorshipThis paper was written while Dr. Yasin Asar visited McMaster University and he was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) , BIDEB-2219 Postdoctoral Research Program, Project No.: 1059B191700537.en_US
dc.identifier.doi10.57805/revstat.v20i5.389
dc.identifier.endpage586en_US
dc.identifier.issn1645-6726
dc.identifier.issn2183-0371
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-85156241759en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage563en_US
dc.identifier.urihttps://doi.org/10.57805/revstat.v20i5.389
dc.identifier.urihttps://hdl.handle.net/20.500.12452/17079
dc.identifier.volume20en_US
dc.identifier.wosWOS:000991822400003en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInst Nacional Estatistica-Ineen_US
dc.relation.ispartofRevstat-Statistical Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBayesian Estimationen_US
dc.subjectEm Algorithmen_US
dc.subjectSem Algorithmen_US
dc.subjectTierney-Kadane's Approximationen_US
dc.subjectProgressively Type-I Hybrid Censoringen_US
dc.subjectWeibull Distributionen_US
dc.titleEstimation in Weibull Distribution Under Progressively Typ e-I Hybrid Censored Dataen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu