Liu-type shrinkage estimations in linear models

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dc.authoridYuzbasi, Bahadir/0000-0002-6196-3201
dc.authoridAsar, Yasin/0000-0003-1109-8456;
dc.authorwosidYuzbasi, Bahadir/F-6907-2013
dc.authorwosidAsar, Yasin/V-5701-2017
dc.authorwosidAhmed, Syed/GSN-7305-2022
dc.contributor.authorYuzbasi, Bahadir
dc.contributor.authorAsar, Yasin
dc.contributor.authorAhmed, S. Ejaz
dc.date.accessioned2024-08-04T20:51:54Z
dc.date.available2024-08-04T20:51:54Z
dc.date.issued2022
dc.departmentİnönü Üniversitesien_US
dc.description.abstractIn this study, we present the preliminary test, Stein-type and positive part Stein-type Liu estimators in the linear models when the parameter vector beta is partitioned into two parts, namely, the main effects beta(1) and the nuisance effects beta(2) such that beta = (beta(1), beta(2)). We consider the case that a priori known or suspected set of the explanatory variables do not contribute to predict the response so that a sub-model maybe enough for this purpose. Thus, the main interest is to estimate beta(1) when beta(2) is close to zero. Therefore, we investigate the performance of the suggested estimators asymptotically and via a Monte Carlo simulation study. Moreover, we present a real data example to evaluate the relative efficiency of the suggested estimators, where we demonstrate the superiority of the proposed estimators.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (NSERC)en_US
dc.description.sponsorshipThe research of S. Ejaz Ahmed was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC).en_US
dc.identifier.doi10.1080/02331888.2022.2055030
dc.identifier.endpage420en_US
dc.identifier.issn0233-1888
dc.identifier.issn1029-4910
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85128055123en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage396en_US
dc.identifier.urihttps://doi.org/10.1080/02331888.2022.2055030
dc.identifier.urihttps://hdl.handle.net/11616/100599
dc.identifier.volume56en_US
dc.identifier.wosWOS:000776150900001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofStatisticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSub-modelen_US
dc.subjectfull modelen_US
dc.subjectpretest and shrinkage estimationen_US
dc.subjectpenalty estimationen_US
dc.subjectMonte Carlo simulationen_US
dc.titleLiu-type shrinkage estimations in linear modelsen_US
dc.typeArticleen_US

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