Developing a restricted two-parameter Liu-type estimator: A comparison of restricted estimators in the binary logistic regression model

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dc.contributor.authorAsar, Yasin
dc.contributor.authorErisoglu, Murat
dc.contributor.authorArashi, Mohammad
dc.date.accessioned2024-02-23T14:20:14Z
dc.date.available2024-02-23T14:20:14Z
dc.date.issued2017
dc.departmentNEÜen_US
dc.description.abstractIn the context of estimating regression coefficients of an ill-conditioned binary logistic regression model, we develop a new biased estimator having two parameters for estimating the regression vector parameter when it is subjected to lie in the linear subspace restriction H = h. The matrix mean squared error and mean squared error (MSE) functions of these newly defined estimators are derived. Moreover, a method to choose the two parameters is proposed. Then, the performance of the proposed estimator is compared to that of the restricted maximum likelihood estimator and some other existing estimators in the sense of MSE via a Monte Carlo simulation study. According to the simulation results, the performance of the estimators depends on the sample size, number of explanatory variables, and degree of correlation. The superiority region of our proposed estimator is identified based on the biasing parameters, numerically. It is concluded that the new estimator is superior to the others in most of the situations considered and it is recommended to the researchers.en_US
dc.identifier.doi10.1080/03610926.2015.1137597
dc.identifier.endpage6873en_US
dc.identifier.issn0361-0926
dc.identifier.issn1532-415X
dc.identifier.issue14en_US
dc.identifier.scopus2-s2.0-85015919406en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage6864en_US
dc.identifier.urihttps://doi.org/10.1080/03610926.2015.1137597
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13071
dc.identifier.volume46en_US
dc.identifier.wosWOS:000400164900012en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_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.subjectLogistic Regressionen_US
dc.subjectMean Squared Erroren_US
dc.subjectMulticollinearityen_US
dc.subjectRestricted Estimatorsen_US
dc.subjectPrimary 62j02en_US
dc.subjectSecondary 62j07en_US
dc.titleDeveloping a restricted two-parameter Liu-type estimator: A comparison of restricted estimators in the binary logistic regression modelen_US
dc.typeArticleen_US

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