The r-d class predictions in linear mixed models

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dc.contributor.authorKuran, Ozge
dc.date.accessioned2024-04-24T17:18:00Z
dc.date.available2024-04-24T17:18:00Z
dc.date.issued2021
dc.departmentDicle Üniversitesien_US
dc.description.abstractIn this paper, we propose the r-d class predictors which are general predictors of the best linear unbiased predictor (BLUP), the principal components regression (PCR) and the Liu predictors in the linear mixed models. Superiorities of the linear combination of the new predictors to each of these predictors are done in the sense of the mean square error matrix criterion. Finally, numerical examples and a simulation study are done to illustrate the findings.en_US
dc.identifier.doi10.1515/jiip-2019-0069
dc.identifier.endpage498en_US
dc.identifier.issn0928-0219
dc.identifier.issn1569-3945
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85088385842
dc.identifier.scopusqualityQ2
dc.identifier.startpage477en_US
dc.identifier.urihttps://doi.org/10.1515/jiip-2019-0069
dc.identifier.urihttps://hdl.handle.net/11468/18531
dc.identifier.volume29en_US
dc.identifier.wosWOS:000704190800001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherWalter De Gruyter Gmbhen_US
dc.relation.ispartofJournal of Inverse and Ill-Posed Problems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMulticollinearityen_US
dc.subjectBest Linear Unbiased Predictoren_US
dc.subjectPrincipal Components Regression Predictoren_US
dc.subjectLiu Predictoren_US
dc.subjectR-D Class Predictoren_US
dc.titleThe r-d class predictions in linear mixed modelsen_US
dc.titleThe r-d class predictions in linear mixed models
dc.typeArticleen_US

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