Publication:
On the weighted mixed liu-type estimator under unbiased stochastic restrictions

dc.contributor.authorYILDIZ, NİLGÜN
dc.contributor.authorsYildiz N.
dc.date.accessioned2022-03-15T02:12:40Z
dc.date.accessioned2026-01-11T16:23:06Z
dc.date.available2022-03-15T02:12:40Z
dc.date.issued2017
dc.description.abstractIn this article, we introduce the weighted mixed Liu-type estimator (WMLTE) based on the weighted mixed and Liu-type estimator (LTE) in linear regression model. We will also present necessary and sufficient conditions for superiority of the weighted mixed Liu-type estimator over the weighted mixed estimator (WME) and Liu type estimator (LTE) in terms of mean square error matrix (MSEM) criterion. Finally, a numerical example and a Monte Carlo simulation is also given to show the theoretical results. © 2017 Taylor & Francis Group, LLC.
dc.identifier.doi10.1080/03610918.2016.1235189
dc.identifier.issn3610918
dc.identifier.urihttps://hdl.handle.net/11424/247808
dc.language.isoeng
dc.publisherTaylor and Francis Inc.
dc.relation.ispartofCommunications in Statistics: Simulation and Computation
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectLiu-type estimators
dc.subjectMean square error matrix
dc.subjectOrdinary mixed estimator
dc.subjectWeighted mixed estimator
dc.subjectWeighted mixed Liu estimator
dc.subjectWeighted mixed Liu-type estimator
dc.titleOn the weighted mixed liu-type estimator under unbiased stochastic restrictions
dc.typearticle
dspace.entity.typePublication
oaire.citation.endPage7248
oaire.citation.issue9
oaire.citation.startPage7238
oaire.citation.titleCommunications in Statistics: Simulation and Computation
oaire.citation.volume46

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