A Gamma-Type Distribution with Applications

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dc.contributor.authorIriarte, Yuri A.
dc.contributor.authorVarela, Hector
dc.contributor.authorGomez, Hector J.
dc.contributor.authorGomez, Hector W.
dc.date2020
dc.date.accessioned2021-04-30T16:34:19Z
dc.date.available2021-04-30T16:34:19Z
dc.description.abstractThis article introduces a new probability distribution capable of modeling positive data that present different levels of asymmetry and high levels of kurtosis. A slashed quasi-gamma random variable is defined as the quotient of independent random variables, a generalized gamma is the numerator, and a power of a standard uniform variable is the denominator. The result is a new three-parameter distribution (scale, shape, and kurtosis) that does not present the identifiability problem presented by the generalized gamma distribution. Maximum likelihood (ML) estimation is implemented for parameter estimation. The results of two real data applications revealed a good performance in real settings.
dc.identifier.citationSYMMETRY-BASEL,Vol.12,,2020
dc.identifier.doi10.3390/sym12050870
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/3029
dc.language.isoen
dc.publisherMDPI
dc.sourceSYMMETRY-BASEL
dc.subject.englishasymmetry
dc.subject.englishgeneralized gamma distribution
dc.subject.englishkurtosis
dc.subject.englishmaximum likelihood estimation
dc.subject.englishslash distribution
dc.titleA Gamma-Type Distribution with Applications
dc.typeArticle
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uct.indizacionSCI
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