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A novel extended Gumbel Type II model with statistical inference and Covid-19 applications

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dc.contributor.author Lone, Showkat Ahmad
dc.contributor.author Sindhu, Tabassum Naz
dc.contributor.author Shafiq, Anum
dc.contributor.author Jarad, Fahd
dc.date.accessioned 2024-02-12T12:30:43Z
dc.date.available 2024-02-12T12:30:43Z
dc.date.issued 2022-04
dc.identifier.citation Lone, Showkat Ahmad;...et.al. (2022). "A novel extended Gumbel Type II model with statistical inference and Covid-19 applications", Results in Physics, Vol.35. tr_TR
dc.identifier.issn 22113797
dc.identifier.uri http://hdl.handle.net/20.500.12416/7163
dc.description.abstract Statistical models play an important role in data analysis, and statisticians are constantly looking for new or relatively new statistical models to fit data sets across a wide range of fields. In this study, we used a new alpha power transformation and the Gumbel Type -II distribution to suggest an unique statistical model. The study contains a simulation analysis to determine the parameters’ efficiency. Two real-life data sets were utilized to demonstrate the use of novel alpha power Gumbel Type II (NAPGT-II) distribution. NAPGT-II distribution yields a better fit than Weibull, new alpha power exponential, exponentiated Gumbel Type-II, Gumbel Type-II and exponentiated generalized Gumbel Type-II distribution, as evidenced by the data. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1016/j.rinp.2022.105377 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject APT tr_TR
dc.subject Average Bias tr_TR
dc.subject Mean Square Error tr_TR
dc.subject NAPGT-II Model tr_TR
dc.subject Root Mean Square Error tr_TR
dc.title A novel extended Gumbel Type II model with statistical inference and Covid-19 applications tr_TR
dc.type article tr_TR
dc.relation.journal Results in Physics tr_TR
dc.contributor.authorID 234808 tr_TR
dc.identifier.volume 35 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen-Edebiyat Fakültesi, Matematik Bölümü tr_TR


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