Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

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datacite.alternateIdentifier.citationSYMMETRY-BASEL,Vol.13,2021
datacite.alternateIdentifier.doi10.3390/sym13112164
datacite.creatorGomez, Hector J.
datacite.creatorGallardo, Diego, I
datacite.creatorSantoro, Karol, I
datacite.date2021
datacite.subject.englishslash distribution
datacite.subject.englishhalf-normal distribution
datacite.subject.englishEM algorithm
datacite.subject.englishtpn package
datacite.titleSlash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm
dc.date.accessioned2022-06-15T20:44:27Z
dc.date.available2022-06-15T20:44:27Z
dc.description.abstractIn this paper, we present an extension of the truncated positive normal (TPN) distribution to model positive data with a high kurtosis. The new model is defined as the quotient between two random variables: the TPN distribution (numerator) and the power of a standard uniform distribution (denominator). The resulting model has greater kurtosis than the TPN distribution. We studied some properties of the distribution, such as moments, asymmetry, and kurtosis. Parameter estimation is based on the moments method, and maximum likelihood estimation uses the expectation-maximization algorithm. We performed some simulation studies to assess the recovery parameters and illustrate the model with a real data application related to body weight. The computational implementation of this work was included in the tpn package of the R software.
dc.identifier.urihttps://repositoriodigital.uct.cl/handle/10925/4597
dc.language.isoen
dc.publisherMDPI
dc.sourceSYMMETRY-BASEL
oaire.resourceTypeArticle
uct.indizacionSCI
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