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Combining the Liu-type estimator and the principal component regression estimator

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dc.contributor.authorİNAN, DENİZ
dc.contributor.authorsInan, Deniz
dc.date.accessioned2022-03-13T12:47:10Z
dc.date.accessioned2026-01-11T10:25:12Z
dc.date.available2022-03-13T12:47:10Z
dc.date.issued2015
dc.description.abstractIn this study a new two-parameter estimator which includes the ordinary least squares, the principal components regression (PCR) and the Liu-type estimator is proposed. Conditions for the superiority of this new estimator over the PCR, r-k class estimator and Liu-type estimator are derived. Furthermore the performance of this estimator is compared with the other estimators in different conditions with simulation studies.
dc.identifier.doi10.1007/s00362-013-0571-5
dc.identifier.eissn1613-9798
dc.identifier.issn0932-5026
dc.identifier.urihttps://hdl.handle.net/11424/238035
dc.identifier.wosWOS:000347837100007
dc.language.isoeng
dc.publisherSPRINGER
dc.relation.ispartofSTATISTICAL PAPERS
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectLiu-type estimator
dc.subjectr-k class estimators
dc.subjectPrincipal component regression estimator
dc.subjectRidge estimator
dc.subjectMulticollinearity
dc.subjectRIDGE-REGRESSION
dc.titleCombining the Liu-type estimator and the principal component regression estimator
dc.typearticle
dspace.entity.typePublication
oaire.citation.endPage156
oaire.citation.issue1
oaire.citation.startPage147
oaire.citation.titleSTATISTICAL PAPERS
oaire.citation.volume56

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