Inference for two Lomax populations under joint type-II censoring

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dc.contributor.authorAsar, Yasin
dc.contributor.authorBelaghi, R. Arabi
dc.date.accessioned2024-02-23T14:20:14Z
dc.date.available2024-02-23T14:20:14Z
dc.date.issued2022
dc.departmentNEÜen_US
dc.description.abstractLomax distribution has been widely used in economics, business and actuarial sciences. Due to its importance, we consider the statistical inference of this model under joint type-II censoring scenario. In order to estimate the parameters, we derive the Newton-Raphson(NR) procedure and we observe that most of the times in the simulation NR algorithm does not converge. Consequently, we make use of the expectation-maximization (EM) algorithm. Moreover, Bayesian estimations are also provided based on squared error, linear-exponential and generalized entropy loss functions together with the importance sampling method due to the structure of posterior density function. In the sequel, we perform a Monte Carlo simulation experiment to compare the performances of the listed methods. Mean squared error values, averages of estimated values as well as coverage probabilities and average interval lengths are considered to compare the performances of different methods. The approximate confidence intervals, bootstrap-p and bootstrap-t confidence intervals are computed for EM estimations. Also, Bayesian coverage probabilities and credible intervals are obtained. Finally, we consider the Bladder Cancer data to illustrate the applicability of the methods covered in the paper.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [BIDEB-2219, 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. We are grateful to Prof. N. Balakrishnan for his guidance and comments.en_US
dc.identifier.doi10.1080/03610918.2020.1814814
dc.identifier.endpage6825en_US
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-85090304697en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage6808en_US
dc.identifier.urihttps://doi.org/10.1080/03610918.2020.1814814
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13070
dc.identifier.volume51en_US
dc.identifier.wosWOS:000566996100001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.ispartofCommunications In Statistics-Simulation And Computationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBayesian Estimationen_US
dc.subjectBootstrap Confidence Intervalsen_US
dc.subjectEm Algorithmen_US
dc.subjectJoint Censoring Schemeen_US
dc.subjectLomax Distributionen_US
dc.subjectMaximum Likelihood Estimationen_US
dc.subjectType-Ii Censoringen_US
dc.titleInference for two Lomax populations under joint type-II censoringen_US
dc.typeArticleen_US

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