A reliability model based on the incomplete generalized integro-exponential function

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dc.contributor.authorAstorga, J.M.
dc.contributor.authorReyes, J.
dc.contributor.authorSantoro, K.I.
dc.contributor.authorVenegas, O.
dc.contributor.authorGómez, H.W.
dc.date.accessioned2024-04-22T23:09:13Z
dc.date.available2024-04-22T23:09:13Z
dc.date.issued2020
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.description.sponsorshipSemillero UA-2020
dc.identifier.doi10.3390/math8091537
dc.identifier.issn2227-7390
dc.identifier.urihttps://repositorioabierto.uantof.cl/handle/uantof/384
dc.language.isoen
dc.publisherMDPI
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceMathematics
dc.subjectgeneralized integro-exponential function
dc.subjectkurtosis
dc.subjectmaximum likelihood
dc.subjectpower muth distribution
dc.subjectslash distribution
dc.titleA reliability model based on the incomplete generalized integro-exponential function
dc.typeArticle
oaire.citation.issue9
oaire.citation.startPage1537
oaire.citation.volume8
organization.identifier.rorhttps://ror.org/04eyc6d95
organization.legalNameUniversidad de Antofagasta
uantof.identificator.departmentDepartamento de Matemáticas
uantof.identificator.facultyFacultad de Ciencias Básicas
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