Unit Maxwell-Boltzmann Distribution and Its Application to Concentrations Pollutant Data

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dc.authoridBakouch, Hassan/0000-0002-3189-0670
dc.authoridAlomair, Gadir/0000-0001-8557-3796
dc.contributor.authorBicer, Cenker
dc.contributor.authorBakouch, Hassan S.
dc.contributor.authorBicer, Hayrinisa Demirci
dc.contributor.authorAlomair, Gadir
dc.contributor.authorHussain, Tassaddaq
dc.contributor.authorAlmohisen, Amal
dc.date.accessioned2025-01-21T16:55:46Z
dc.date.available2025-01-21T16:55:46Z
dc.date.issued2024
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn the vast statistical literature, there are numerous probability distribution models that can model data from real-world phenomena. New probability models, nevertheless, are still required in order to represent data with various spread behaviors. It is a known fact that there is a great need for new models with limited support. In this study, a flexible probability model called the unit Maxwell-Boltzmann distribution, which can model data values in the unit interval, is derived by selecting the Maxwell-Boltzmann distribution as a base-line model. The important characteristics of the derived distribution in terms of statistics and mathematics are investigated in detail in this study. Furthermore, the inference problem for the mentioned distribution is addressed from the perspectives of maximum likelihood, method of moments, least squares, and maximum product space, and different estimators are obtained for the unknown parameter of the distribution. The derived distribution outperforms competitive models according to different fit tests and information criteria in the applications performed on four actual air pollutant concentration data sets, indicating that it is an effective model for modeling air pollutant concentration data.
dc.description.sponsorshipDeanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia; [5791]
dc.description.sponsorshipThis work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. 5791].
dc.identifier.doi10.3390/axioms13040226
dc.identifier.issn2075-1680
dc.identifier.issue4
dc.identifier.urihttps://doi.org/10.3390/axioms13040226
dc.identifier.urihttps://hdl.handle.net/20.500.12587/25837
dc.identifier.volume13
dc.identifier.wosWOS:001210084500001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofAxioms
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjecthazard function; Maxwell-Boltzmann; characterizations; estimation; simulation; application
dc.titleUnit Maxwell-Boltzmann Distribution and Its Application to Concentrations Pollutant Data
dc.typeArticle

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