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Gibbs sampling approach to variable selection in linear regression with outlier values

dc.contributor.authorYardımcı, Atilla
dc.contributor.authorErar, Aydın
dc.date.accessioned2025-01-09T20:08:20Z
dc.date.available2025-01-09T20:08:20Z
dc.date.issued2005
dc.identifier.issn2147-1762
dc.identifier.urihttps://hdl.handle.net/20.500.14124/8149
dc.description.abstractIn this study, Gibbs sampling has been applied to the variable selection in the linear regression model with outlier values. Gibbs sampling has been compared with classical variable selection criteria by using dummy data with different beta and priors.en_US
dc.description.abstractBu çalışmada, aykırı değerlerin olduğu doğrusal regresyon modelinde değişken seçimine, Gibbs örneklemesi yaklaşımı uygulanmıştır. Klasik değişken seçimi ölçütleri ile Gibbs örneklemesi yaklaşımı, değişik $\beta$ ve önsel yapıları için yapay veriler üzerinden karşılaştırılmıştır.
dc.language.isoengen_US
dc.publisherGazi Univen_US
dc.relation.ispartofGazi University Journal of Scienceen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBayesian variable selectionen_US
dc.subjectprior distributionen_US
dc.subjectGibbs samplingen_US
dc.subjectMarkov Chain Monte Carloen_US
dc.subjectoutlier valuesen_US
dc.subjectentropyen_US
dc.titleGibbs sampling approach to variable selection in linear regression with outlier valuesen_US
dc.typearticleen_US
dc.departmentMimar Sinan Güzel Sanatlar Üniversitesien_US
dc.identifier.startpage603en_US
dc.identifier.endpage611en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.wosqualityN/A
dc.identifier.wosWOS:000420948900006
dc.identifier.trdizinidTkRnd01qYzM/gibb
dc.indekslendigikaynakWeb of Scienceen_US


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