A Power Maxwell Distribution with Heavy Tails and Applications
datacite.alternateIdentifier.citation | MATHEMATICS,Vol.8,,2020 | |
datacite.alternateIdentifier.doi | 10.3390/math8071116 | |
datacite.creator | Segovia, Francisco A. | |
datacite.creator | Gomez, Yolanda M. | |
datacite.creator | Venegas, Osvaldo | |
datacite.creator | Gomez, Hector W. | |
datacite.date | 2020 | |
datacite.subject.english | Maxwell distribution | |
datacite.subject.english | slash distribution | |
datacite.subject.english | kurtosis | |
datacite.subject.english | maximum likelihood | |
datacite.subject.english | EM algorithm | |
datacite.title | A Power Maxwell Distribution with Heavy Tails and Applications | |
dc.date.accessioned | 2021-04-30T16:47:51Z | |
dc.date.available | 2021-04-30T16:47:51Z | |
dc.description.abstract | In this paper we introduce a distribution which is an extension of the power Maxwell distribution. This new distribution is constructed based on the quotient of two independent random variables, the distributions of which are the power Maxwell distribution and a function of the uniform distribution (0,1) respectively. Thus the result is a distribution with greater kurtosis than the power Maxwell. We study the general density of this distribution, and some properties, moments, asymmetry and kurtosis coefficients. Maximum likelihood and moments estimators are studied. We also develop the expectation-maximization algorithm to make a simulation study and present two applications to real data. | |
dc.identifier.uri | http://repositoriodigital.uct.cl/handle/10925/3598 | |
dc.language.iso | en | |
dc.publisher | MDPI | |
dc.source | MATHEMATICS | |
oaire.resourceType | Article | |
uct.catalogador | WOS | |
uct.indizacion | SCI |