A novel chen extension: Theory, characterizations and different estimation methods

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dc.contributor.authorYousof, Haitham M.
dc.contributor.authorKorkmaz, Mustafa Çağatay
dc.contributor.authorHamedani G.G.
dc.contributor.authorIbrahim, Mohamed
dc.date.accessioned2025-07-11T11:09:54Z
dc.date.available2025-07-11T11:09:54Z
dc.date.issued2022
dc.departmentAÇÜ, Eğitim Fakültesi, Eğitim Bilimleri Bölümü
dc.description.abstractIn this work, we derive a novel extension of Chen distribution. Some statistical properties of the new model are derived. Numerical analysis for mean, variance, skewness and kurtosis is presented. Some characterizations of the proposed distribution are presented. Different classical estimation methods under uncensored schemes such as the maximum likelihood, Anderson-Darling, weighted least squares and right-tail Anderson–Darling methods are considered. Simulation studies are performed in order to compare and assess the above-mentioned estimation methods. For comparing the applicability of the four classical methods, two application to real data set are analyzed.
dc.identifier.doi10.28924/ada/stat.2.1
dc.identifier.issn28060954
dc.identifier.scopuss2.0-85128697462
dc.identifier.scopusqualityQ4
dc.identifier.urihttps://hdl.handle.net/11494/5766
dc.identifier.volume2
dc.indekslendigikaynakScopus
dc.institutionauthorKorkmaz, Mustafa Çağatay
dc.language.isoen
dc.publisherAda Academica
dc.relation.ispartofEuropean Journal of Statistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAnderson-Darling
dc.subjectCharacterizations
dc.subjectChen model
dc.subjectStatistical modeling
dc.subjectWeighted least squares
dc.titleA novel chen extension: Theory, characterizations and different estimation methods
dc.typeArticle

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