A Note on Pareto-Type Distributions Parameterized by Its Mean and Precision Parameters

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datacite.creatorBourguignon, Marcelo
datacite.creatorGallardo, Diego
datacite.creatorGómez, Héctor
datacite.date2022-02-08
datacite.rightsAcceso Abierto
datacite.subject.englishModeling
datacite.subject.englishParameterization
datacite.subject.englishPareto-type distributions
datacite.subject.englishVarying precision
datacite.titleA Note on Pareto-Type Distributions Parameterized by Its Mean and Precision Parameters
dc.date.accessioned2024-11-21T14:47:28Z
dc.date.available2024-11-21T14:47:28Z
dc.descriptionLa investigación de Héctor J. Gómez fue financiada por el Fondo de Apoyo a la Innovación en Educación Superior, Universidad Católica de Temuco, UCT19101.
dc.description.abstractenPareto-type distributions are well-known distributions used to fit heavy-tailed data. How-ever, the standard parameterizations used for Pareto-type distributions are poorly suited to modeling. On this note, we suggest new parameterizations that are better suited to the purpose. In addition, we propose many regression models where the response variable is Pareto-type distributed using new parameterizations that are indexed by mean and precision parameters. The main motivation for these new parametrizations is the useful interpretation of the regression coefficients in terms of the mean and precision, as is usual in the context of regression models. The parameter estimation of these new models is performed, based on the maximum likelihood paradigm. Some numerical illustrations of the estimators are presented with a discussion of the obtained results. Finally, we illustrate the practicality of the new models by means of two applications to real data sets.
dc.identifier.doi10.3390/math10030528
dc.identifier.urihttps://repositoriodigital.uct.cl/handle/10925/6040
dc.language.isoen
dc.rightsArtículo de acceso abierto, bajo los términos y condiciones de la licencia Creative Commons Attribution (CC BY) (https://creativecommons.org/licenses/by/4.0/).
dc.sourceMathematics
oaire.citationIssue3
oaire.citationTitleArtículo
oaire.citationVolume10
oaire.resourceTypeArtículo
uct.catalogadormlj
uct.departamentoDepartamento Ciencias Matematicas y Fisicas
uct.facultadFacultad de Ingeniería
uct.indizacionSCOPUS
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