The Lomax regression model with residual analysis: an application to insurance data

dc.contributor.authorAltun, Emrah
dc.date.accessioned2025-10-18T13:22:49Z
dc.date.created2020
dc.date.issued2020
dc.departmentFakülteler, Fen Fakültesi, Matematik Bölümü
dc.description.abstractIn this paper, we introduce a new regression model, calledLomax regression model, as an alternative to the gamma regression model. The maximum-likelihood method is used to estimate the unknown parameters of the proposed model, and the finite sample performance of the maximum-likelihood estimation method is evaluated by means of the Monte-Carlo simulation study. The randomized quantile residuals are used to check the adequacy of the fitted model. The insurance data are analyzed to demonstrate the usefulness of the proposed regression model against the gamma regression model.
dc.identifier.doi10.1080/02664763.2020.1834515
dc.identifier.endpage2524
dc.identifier.issn0266-4763
dc.identifier.issn1360-0532
dc.identifier.issue13-15
dc.identifier.pmid35707103
dc.identifier.scopus2-s2.0-85092777873
dc.identifier.scopusqualityQ2
dc.identifier.startpage2515
dc.identifier.urihttps://doi.org/10.1080/02664763.2020.1834515
dc.identifier.urihttps://hdl.handle.net/11772/22535
dc.identifier.volume48
dc.identifier.wosWOS:000579667400001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherTaylor & Francis Ltd
dc.relation.ispartofJournal of Applied Statistics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzWoS_20251016
dc.subjectLomax Distribution
dc.subjectHeteroscedasticity
dc.subjectMaximum Likelihood
dc.subjectGamma Regression
dc.subjectInsurance Loss
dc.titleThe Lomax regression model with residual analysis: an application to insurance data
dc.typeArticle
dspace.entity.typePublication

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