Percentile Estimators for Two-Component Mixture Distribution Models

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dc.contributor.authorErisoglu, Ulku
dc.contributor.authorErisoglu, Murat
dc.date.accessioned2024-02-23T14:00:11Z
dc.date.available2024-02-23T14:00:11Z
dc.date.issued2019
dc.departmentNEÜen_US
dc.description.abstractThe percentile estimators have a widespread usage in the estimation of distribution parameters because of simplicity and ease of computation. In this study, we investigate the percentile method for two-component mixture distribution models which are commonly used in modeling of heterogeneous univariate data sets. We have proposed percentile estimator for two-component mixture Weibull and two-component mixture Rayleigh distributions according to two different approaches. Performances of the defined percentile estimators were compared with maximum likelihood estimators using simulation. For this purpose, we used several criteria which are bias, mean squared error, mean absolute deviation, mean relative total error and running time of the algorithm. The benefits of the proposed methods have been illustrated by three different real data sets.en_US
dc.identifier.doi10.1007/s40995-018-0522-z
dc.identifier.endpage619en_US
dc.identifier.issn1028-6276
dc.identifier.issn2364-1819
dc.identifier.issueA2en_US
dc.identifier.scopus2-s2.0-85063012553en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage601en_US
dc.identifier.urihttps://doi.org/10.1007/s40995-018-0522-z
dc.identifier.urihttps://hdl.handle.net/20.500.12452/11495
dc.identifier.volume43en_US
dc.identifier.wosWOS:000461317600027en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer International Publishing Agen_US
dc.relation.ispartofIranian Journal Of Science And Technology Transaction A-Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPercentilesen_US
dc.subjectMixture Distributionen_US
dc.subjectEm Algorithmen_US
dc.subjectMaximum Likelihooden_US
dc.subjectMulti-Modalityen_US
dc.subject62f10en_US
dc.subject60e05en_US
dc.subject62-07en_US
dc.titlePercentile Estimators for Two-Component Mixture Distribution Modelsen_US
dc.typeArticleen_US

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