Marginal ridge conceptual predictive model selection criterion in linear mixed models

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dc.contributor.authorKuran, Ozge
dc.contributor.authorOzkale, M. Revan
dc.date.accessioned2024-04-24T16:24:35Z
dc.date.available2024-04-24T16:24:35Z
dc.date.issued2021
dc.departmentDicle Üniversitesien_US
dc.description.abstractIn linear mixed model selection under ridge regression, we propose the model selection criteria based on conceptual predictive () statistic.The first proposed criterion is marginal ridge C-p () statistic based on the expected marginal Gauss discrepancy. An improvement of MRCp (IMRCp) statistic is then suggested and demonstrated, which is also an asymptotically unbiased estimator of the expected marginal Gauss discrepancy. Finally, a real data analysis and a Monte Carlo simulation study are given to examine the performance of the proposed criteria.en_US
dc.identifier.doi10.1080/03610918.2018.1563155
dc.identifier.endpage607en_US
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85060636600en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage581en_US
dc.identifier.urihttps://doi.org/10.1080/03610918.2018.1563155
dc.identifier.urihttps://hdl.handle.net/11468/16780
dc.identifier.volume50en_US
dc.identifier.wosWOS:000497636000001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherTaylor & Francis Incen_US
dc.relation.ispartofCommunications in Statistics-Simulation and Computationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLinear Mixed Model Selectionen_US
dc.subjectMarginal Gauss Discrepancyen_US
dc.subjectMarginal Ridge Cpen_US
dc.subjectMulticollinearityen_US
dc.subjectRidge Regressionen_US
dc.titleMarginal ridge conceptual predictive model selection criterion in linear mixed modelsen_US
dc.typeArticleen_US

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