A Compound Class of Inverse-Power Muth and Power Series Distributions

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datacite.alternateIdentifier.citationAXIOMS,Vol.12,,2023
datacite.alternateIdentifier.doi10.3390/axioms12040383
datacite.creatorBarrios Blanco, Leonardo
datacite.creatorGallardo, Diego I.
datacite.creatorGomez, Hector J.
datacite.creatorBourguignon, Marcelo
datacite.date2023
datacite.subject.englishEM algorithm
datacite.subject.englishinverse-power Muth distribution
datacite.subject.englishlikelihood
datacite.subject.englishpower series distribution
datacite.titleA Compound Class of Inverse-Power Muth and Power Series Distributions
dc.date.accessioned2023-06-08T15:48:12Z
dc.date.available2023-06-08T15:48:12Z
dc.description.abstractThis paper introduces the inverse-power Muth power series model, which is a composition of the inverse-power Muth and the class of power series distributions. The use of the Bell distribution in this context is emphasized for the first time in the literature. Probability density, survival and hazard functions are studied, as well as their moments. Using the stochastic representation of the model, the maximum-likelihood estimators are implemented by the use of the expectation-maximization algorithm, while standard errors are calculated using Oakes' method. Monte Carlo simulation studies are conducted to show the performance of the maximum-likelihood estimators in finite samples. Two applications to real datasets are shown, where our proposal is compared with some models based on power series compositions.
dc.identifier.urihttps://repositoriodigital.uct.cl/handle/10925/5274
dc.language.isoen
dc.publisherMDPI
dc.sourceAXIOMS
oaire.resourceTypeArticle
uct.indizacionSCI
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