A new kernel two-parameter prediction under multicollinearity in partially linear mixed measurement error model

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dc.authoridKuran, Ozge/0000-0001-5632-001X
dc.contributor.authorYalaz, Secil
dc.contributor.authorKuran, Ozge
dc.date.accessioned2025-02-22T14:08:57Z
dc.date.available2025-02-22T14:08:57Z
dc.date.issued2024
dc.departmentDicle Üniversitesien_US
dc.description.abstractA Partially linear mixed effects model relating a response Y to predictors $ (X,Z,T) $ (X,Z,T) with the mean function $ X<^>{T}\beta +Zb+g(T) $ XT beta+Zb+g(T) is considered in this paper. When the parametric parts' variable X are measured with additive error and there is ill-conditioned data suffering from multicollinearity, a new kernel two-parameter prediction method using the kernel ridge and Liu regression approach is suggested. The kernel two parameter estimator of beta and the predictor of b are derived by modifying the likelihood and Henderson methods. Matrix mean square error comparisons are calculated. We also demonstrate that under suitable conditions, the resulting estimator of beta is asymptotically normal. The situation with an unknown measurement error covariance matrix is handled. A Monte Carlo simulation study, together with an earthquake data example, is compiled to evaluate the effectiveness of the proposed approach at the end of the paper.en_US
dc.identifier.doi10.1080/02331888.2024.2378301
dc.identifier.endpage748en_US
dc.identifier.issn0233-1888
dc.identifier.issn1029-4910
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85198540312en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage723en_US
dc.identifier.urihttps://doi.org/10.1080/02331888.2024.2378301
dc.identifier.urihttps://hdl.handle.net/11468/29730
dc.identifier.volume58en_US
dc.identifier.wosWOS:001271089800001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofStatisticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250222
dc.subjectQ. Zhuen_US
dc.subjectPartially linear mixed modelen_US
dc.subjectmeasurement erroren_US
dc.subjectmulticollinearityen_US
dc.subjectkernel ridge predictionen_US
dc.subjectkernel liu predictionen_US
dc.titleA new kernel two-parameter prediction under multicollinearity in partially linear mixed measurement error modelen_US
dc.typeArticleen_US

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