An improved and efficient biased estimation technique in logistic regression model

dc.contributor.authorAsar, Yasin
dc.contributor.authorWu, Jibo
dc.date.accessioned2024-02-23T14:20:14Z
dc.date.available2024-02-23T14:20:14Z
dc.date.issued2020
dc.departmentNEÜen_US
dc.description.abstractIn this article, we propose a new improved and efficient biased estimation method which is a modified restricted Liu-type estimator satisfying some sub-space linear restrictions in the binary logistic regression model. We study the properties of the new estimator under the mean squared error matrix criterion and our results show that under certain conditions the new estimator is superior to some other estimators. Moreover, a Monte Carlo simulation study is conducted to show the performance of the new estimator in the simulated mean squared error and predictive median squared errors sense. Finally, a real application is considered.en_US
dc.identifier.doi10.1080/03610926.2019.1568494
dc.identifier.endpage2252en_US
dc.identifier.issn0361-0926
dc.identifier.issn1532-415X
dc.identifier.issue9en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage2237en_US
dc.identifier.urihttps://doi.org/10.1080/03610926.2019.1568494
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13074
dc.identifier.volume49en_US
dc.identifier.wosWOS:000519155600012en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.ispartofCommunications In Statistics-Theory And Methodsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRestricted Maximum Likelihood Estimatoren_US
dc.subjectRestricted Liu-Type Estimatoren_US
dc.subjectModified Restricted Liu-Type Estimatoren_US
dc.subjectLogistic Regression Modelen_US
dc.titleAn improved and efficient biased estimation technique in logistic regression modelen_US
dc.typeArticleen_US

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