Generalized Kibria-Lukman Prediction Approximation in Linear Mixed Models

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dc.contributor.authorKuran, Özge
dc.date.accessioned2025-02-22T14:18:02Z
dc.date.available2025-02-22T14:18:02Z
dc.date.issued2024
dc.departmentDicle Üniversitesien_US
dc.description.abstractOne of the new suggested prediction method is the Kibria-Lukman's prediction approach under multicollinearity in linear mixed models and in this article, the generalized Kibria-Lukman estimator and predictor are introduced to combat multicollinearity problem. The comparisons between the proposed generalized Kibria-Lukman estimator/predictor and several other estimators/predictors, namely the best linear unbiased estimator/predictor and Kibria-Lukman estimator/predictor are done by using the matrix mean square error criterion. Lastly, the selection of the biasing parameter is given and to demonstrate the performance of our new de ned prediction method, the greenhouse gases data analysis is made.en_US
dc.identifier.endpage35en_US
dc.identifier.issn2717-6185
dc.identifier.issue1en_US
dc.identifier.startpage25en_US
dc.identifier.trdizinid1225649en_US
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1225649
dc.identifier.urihttps://hdl.handle.net/11468/30232
dc.identifier.volume5en_US
dc.indekslendigikaynakTr-Dizinen_US
dc.institutionauthorKuran, Özge
dc.language.isoenen_US
dc.relation.ispartofFundamentals of contemporary mathematical sciences (Online)en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKA_TR_20250222
dc.subjectMean square erroren_US
dc.subjectmulticollinearityen_US
dc.subjectLinear mixed modelen_US
dc.subjectgeneralized Kibria-Lukman predictoren_US
dc.titleGeneralized Kibria-Lukman Prediction Approximation in Linear Mixed Modelsen_US
dc.typeArticleen_US

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