ESTIMATING THE MISSING VALUE IN ONE-WAY ANOVA UNDER LONG-TAILED SYMMETRIC ERROR DISTRIBUTIONS

dc.contributor.authorAydin, Demet
dc.contributor.authorSenoglu, Birdal
dc.date.accessioned2025-03-23T19:48:04Z
dc.date.available2025-03-23T19:48:04Z
dc.date.issued2018
dc.departmentSinop Üniversitesi
dc.description.abstractIn practice, missing values are widely seen and create serious problems in almost all statistical analysis. In this study, to deal with missing values, we propose estimators for missing value in one-way analysis of variance (ANOVA) when the distribution of error terms is long-tailed symmetric (LTS). We use methodologies known as maximum likelihood (ML), modified maximum likelihood (MML) and least squares (LS) in estimating missing value. Expectation and maximization (EM) algorithm is used for computing ML estimate of missing value. We compare the efficiencies of LS, ML and MML estimators of missing value via Monte Carlo simulation study. Simulation results show that ML estimator of missing value is the most efficient among the others. The usefulness of the proposed estimators is illustrated by peak discharge data example taken from civil engineering.
dc.identifier.endpage538
dc.identifier.issn1304-7205
dc.identifier.issn1304-7191
dc.identifier.issue2
dc.identifier.scopusqualityN/A
dc.identifier.startpage523
dc.identifier.urihttps://hdl.handle.net/11486/7501
dc.identifier.volume36
dc.identifier.wosWOS:000437057300018
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherYildiz Technical Univ
dc.relation.ispartofSigma Journal of Engineering and Natural Sciences-Sigma Muhendislik Ve Fen Bilimleri Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectMissing value
dc.subjectone-way ANOVA
dc.subjectLTS distribution
dc.subjectEM algorithm
dc.subjectMML methodology
dc.titleESTIMATING THE MISSING VALUE IN ONE-WAY ANOVA UNDER LONG-TAILED SYMMETRIC ERROR DISTRIBUTIONS
dc.typeArticle

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