A parametric quantile regression model for asymmetric response variables on the real line

dc.contributor.authorGallardo, D.I.
dc.contributor.authorBourguignon, M.
dc.contributor.authorGalarza, C.E.
dc.contributor.authorGómez, H.W.
dc.date.accessioned2024-04-22T23:09:08Z
dc.date.available2024-04-22T23:09:08Z
dc.date.issued2020
dc.description.abstractIn this paper, we introduce a novel parametric quantile regression model for asymmetric response variables, where the response variable follows a power skew-normal distribution. By considering a new convenient parametrization, these distribution results are very useful for modeling different quantiles of a response variable on the real line. The maximum likelihood method is employed to estimate the model parameters. Besides, we present a local influence study under different perturbation settings. Some numerical results of the estimators in finite samples are illustrated. In order to illustrate the potential for practice of our model, we apply it to a real dataset
dc.description.sponsorshipGrant PUENTE UA, Chile
dc.identifier.doi10.3390/sym12121938
dc.identifier.issn2073-8994
dc.identifier.urihttps://repositorioabierto.uantof.cl/handle/uantof/380
dc.language.isoen
dc.publisherMDPI
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceSymmetry
dc.subjectasymmetric data
dc.subjectparametric inference
dc.subjectquantile regression model
dc.subjectskew-normal distributions
dc.titleA parametric quantile regression model for asymmetric response variables on the real line
dc.typeArticle
oaire.citation.endPage16
oaire.citation.issue1938
oaire.citation.startPage1
oaire.citation.volume12
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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