A New Generalization of the Truncated Gumbel Distribution with Quantile Regression and Applications

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datacite.alternateIdentifier.citationMATHEMATICS,Vol.12,2024
datacite.alternateIdentifier.doi10.3390/math12111762
datacite.creatorGomez, Hector J.
datacite.creatorSantoro, Karol I.
datacite.creatorAyma, Diego
datacite.creatorCortes, Isaac E.
datacite.creatorGallardo, Diego I.
datacite.creatorMagalhaes, Tiago M.
datacite.date2024
datacite.subject.englishGumbel distribution
datacite.subject.englishmaximum likelihood estimators
datacite.subject.englishquantile regression
datacite.subject.englishtruncated distribution
datacite.titleA New Generalization of the Truncated Gumbel Distribution with Quantile Regression and Applications
dc.date.accessioned2024-09-10T18:47:12Z
dc.date.available2024-09-10T18:47:12Z
dc.description.abstractIn this article, we introduce a new model with positive support. This model is an extension of the truncated Gumbel distribution, where a shape parameter is incorporated that provides greater flexibility to the new model. The model is parameterized in terms of the p-th quantile of the distribution to perform quantile regression in this model. An extensive simulation study demonstrates the good performance of the maximum likelihood estimators in finite samples. Finally, two applications to real datasets related to the level of beta-carotene and body mass index are presented.
dc.identifier.urihttps://repositoriodigital.uct.cl/handle/10925/5984
dc.language.isoen
dc.publisherMDPI
dc.sourceMATHEMATICS
oaire.resourceTypeArticle
uct.indizacionSCI
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