Model selection via conditional conceptual predictive statistic for mixed and stochastic restricted ridge estimators in linear mixed models

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dc.authorid0000-0001-7085-7403en_US
dc.authorid0000-0001-5632-001Xen_US
dc.contributor.authorÖzkale, M. Revan
dc.contributor.authorKuran, Özge
dc.date.accessioned2024-03-19T12:55:43Z
dc.date.available2024-03-19T12:55:43Z
dc.date.issued2022en_US
dc.departmentDicle Üniversitesi, Fen Fakültesi, İstatistik Bölümüen_US
dc.description.abstractIn this article, we characterize the mixed (Formula presented.) ((Formula presented.)) and conditional stochastic restricted ridge (Formula presented.) ((Formula presented.)) statistics that depend on the expected conditional Gauss discrepancy for the purpose of selecting the most appropriate model when stochastic restrictions are appeared in linear mixed models. Under the known and unknown variance components assumptions, we define two shapes of (Formula presented.) and (Formula presented.) statistics. Then, the article is concluded with both a Monte Carlo simulation study and a real data analysis, supporting the findings of the theoretical results on the (Formula presented.) and (Formula presented.) statistics.en_US
dc.identifier.citationÖzkale, M. R. ve Kuran, Ö. (2022). Model selection via conditional conceptual predictive statistic for mixed and stochastic restricted ridge estimators in linear mixed models. Concurrency and Computation: Practice and Experience, 34(28), 1-35.en_US
dc.identifier.doi10.1002/cpe.7366en_US
dc.identifier.endpage35en_US
dc.identifier.issn1532-0626
dc.identifier.issue28en_US
dc.identifier.scopus2-s2.0-85139412367en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/epdf/10.1002/cpe.7366
dc.identifier.urihttps://hdl.handle.net/11468/13640
dc.identifier.volume34en_US
dc.identifier.wosWOS:000865074800001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorKuran, Özge
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Ltden_US
dc.relation.ispartofConcurrency and Computation: Practice and Experienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGauss discrepancyen_US
dc.subjectInformation criterionen_US
dc.subjectMallow's conceptual predictive statisticen_US
dc.subjectModel selectionen_US
dc.subjectRandom effectsen_US
dc.titleModel selection via conditional conceptual predictive statistic for mixed and stochastic restricted ridge estimators in linear mixed modelsen_US
dc.typeArticleen_US

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