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Matrix mean squared error comparisons of some biased estimators with two biasing parameters

dc.contributor.authorKurnaz, Fatma Sevinc
dc.contributor.authorAkay, Kadri Ulas
dc.date.accessioned2026-06-27T14:10:43Z
dc.date.issued2018
dc.description.abstractTo deal with multicollinearity problem, the biased estimators with two biasing parameters have recently attracted much research interest. The aim of this article is to compare one of the last proposals given by Yang and Chang (2010) with Liu-type estimator (Liu 2003) and k - d class estimator (Sakallioglu and Kaciranlar 2008) under the matrix mean squared error criterion. As well as giving these comparisons theoretically, we support the results with the extended simulation studies and real data example, which show the advantages of the proposal given by Yang and Chang (2010) over the other proposals with increasing multicollinearity level.en
dc.description.urihttps://doi.org/10.1080/03610926.2017.1335415
dc.identifier.doi10.1080/03610926.2017.1335415
dc.identifier.eissn1532-415X
dc.identifier.endpage2035
dc.identifier.issn0361-0926
dc.identifier.issue8
dc.identifier.startpage2022
dc.identifier.urihttps://hdl.handle.net/20.500.14981/57610
dc.identifier.volume47
dc.identifier.wos000424160100018
dc.language.isoeng
dc.publisherTAYLOR & FRANCIS INC
dc.relation.ispartofCOMMUNICATIONS IN STATISTICS-THEORY AND METHODS
dc.subjectBiased estimators
dc.subjectk - d class estimator
dc.subjectLiu-type estimator
dc.subjectMatrix mean squared error
dc.subjectMulticollinearity
dc.subjectRIDGE-REGRESSION
dc.subjectLINEAR-REGRESSION
dc.subjectMathematics
dc.titleMatrix mean squared error comparisons of some biased estimators with two biasing parameters
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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