A Reliability Model Based on the Incomplete Generalized Integro-Exponential Function

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dc.contributor.authorAstorga, Juan M.
dc.contributor.authorReyes, Jimmy
dc.contributor.authorSantoro, Karol, I
dc.contributor.authorVenegas, Osvaldo
dc.contributor.authorGomez, Hector W.
dc.date2020
dc.date.accessioned2021-04-30T16:59:15Z
dc.date.available2021-04-30T16:59:15Z
dc.description.abstractThis article introduces an extension of the Power Muth (PM) distribution for modeling positive data sets with a high coefficient of kurtosis. The resulting distribution has greater kurtosis than the PM distribution. We show that the density can be represented based on the incomplete generalized integro-exponential function. We study some of its properties and moments, and its coefficients of asymmetry and kurtosis. We apply estimations using the moments and maximum likelihood methods and present a simulation study to illustrate parameter recovery. The results of application to two real data sets indicate that the new model performs very well in the presence of outliers.
dc.identifier.citationMATHEMATICS,Vol.8,,2020
dc.identifier.doi10.3390/math8091537
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/3774
dc.language.isoen
dc.publisherMDPI
dc.sourceMATHEMATICS
dc.subject.englishgeneralized integro-exponential function
dc.subject.englishkurtosis
dc.subject.englishmaximum likelihood
dc.subject.englishpower muth distribution
dc.subject.englishslash distribution
dc.titleA Reliability Model Based on the Incomplete Generalized Integro-Exponential Function
dc.typeArticle
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uct.indizacionSCI
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