Heterogeneous data modeling with two-component Weibull-Poisson distribution

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dc.contributor.authorErisoglu, Ulku
dc.contributor.authorErisoglu, Murat
dc.contributor.authorCalis, Nazif
dc.date.accessioned2024-02-23T14:17:17Z
dc.date.available2024-02-23T14:17:17Z
dc.date.issued2013
dc.departmentNEÜen_US
dc.description.abstractThe mixture distribution models are more useful than pure distributions in modeling of heterogeneous data sets. The aim of this paper is to propose mixture of Weibull-Poisson (WP) distributions to model heterogeneous data sets for the first time. So, a powerful alternative mixture distribution is created for modeling of the heterogeneous data sets. In the study, many features of the proposed mixture of WP distributions are examined. Also, the expectation maximization (EM) algorithm is used to determine the maximum-likelihood estimates of the parameters, and the simulation study is conducted for evaluating the performance of the proposed EM scheme. Applications for two real heterogeneous data sets are given to show the flexibility and potentiality of the new mixture distribution.en_US
dc.identifier.doi10.1080/02664763.2013.818108
dc.identifier.endpage2461en_US
dc.identifier.issn0266-4763
dc.identifier.issn1360-0532
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-84885375591en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage2451en_US
dc.identifier.urihttps://doi.org/10.1080/02664763.2013.818108
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13036
dc.identifier.volume40en_US
dc.identifier.wosWOS:000325124800010en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofJournal Of Applied Statisticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEm Algorithmen_US
dc.subjectHeterogeneous Dataen_US
dc.subjectMixture Of Wp Distributionsen_US
dc.subjectMixed Distributionen_US
dc.subjectFatigueen_US
dc.subjectOral Irrigatorsen_US
dc.titleHeterogeneous data modeling with two-component Weibull-Poisson distributionen_US
dc.typeArticleen_US

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