Linear mixed models with skew-elliptical distributions: A Bayesian approach

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dc.contributor.authorJara, Alejandro
dc.contributor.authorQuintana, Fernando
dc.contributor.authorMartin, Ernesto San
dc.date.accessioned2024-01-10T13:14:22Z
dc.date.available2024-01-10T13:14:22Z
dc.date.issued2008
dc.description.abstractNormality of random effects and error terms is a routine assumption for linear mixed models. However, such an assumption may be unrealistic, obscuring important features of within- and among-unit variation. A simple and robust Bayesian parametric approach that relaxes this assumption by using a multivariate skew-elliptical distribution, which includes the Skew-t, Skew-normal, t-Student, and Normal distributions as special cases and provides flexibility in capturing a broad range of non-normal and asymmetric behavior is presented. An appropriate posterior simulation scheme is developed and the methods are illustrated with an application to a longitudinal data example. (C) 2008 Elsevier B.V. All rights reserved.
dc.fechaingreso.objetodigital2024-04-09
dc.format.extent13 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.csda.2008.04.027
dc.identifier.eissn1872-7352
dc.identifier.issn0167-9473
dc.identifier.urihttps://doi.org/10.1016/j.csda.2008.04.027
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/78400
dc.identifier.wosidWOS:000258259600014
dc.information.autorucMatemática;Quintana F;S/I;100343
dc.information.autorucMatemática;San Martín E;S/I;1001052
dc.issue.numero11
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final5045
dc.pagina.inicio5033
dc.publisherELSEVIER SCIENCE BV
dc.revistaCOMPUTATIONAL STATISTICS & DATA ANALYSIS
dc.rightsacceso restringido
dc.subjectLONGITUDINAL DATA
dc.subjectT-DISTRIBUTION
dc.subjectREGRESSION-MODELS
dc.subjectMULTIVARIATE
dc.subjectCOMPUTATION
dc.subjectPOPULATION
dc.subjectPITFALLS
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleLinear mixed models with skew-elliptical distributions: A Bayesian approach
dc.typeartículo
dc.volumen52
sipa.codpersvinculados100343
sipa.codpersvinculados1001052
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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