Skew normal measurement error models

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dc.contributor.authorArellano Valle, RB
dc.contributor.authorOzan, S
dc.contributor.authorBolfarine, H
dc.contributor.authorLachos, VH
dc.date.accessioned2024-01-10T12:08:36Z
dc.date.available2024-01-10T12:08:36Z
dc.date.issued2005
dc.description.abstractIn this paper we define a class of skew normal measurement error models, extending usual symmetric normal models in order to avoid data transformation. The likelihood function of the observed data is obtained, which can be maximized by using existing statistical software. Inference on the parameters of interest can be approached by using the observed information matrix, which can also be computed by using existing statistical software, such as the Ox program. Bayesian inference is also discussed for the family of asymmetric models in terms of invariance with respect to the symmetric normal distribution showing that early results obtained for the normal distribution also holds for the asymmetric family. Results of a simulation study and an analysis of a real data set analysis are provided. (c) 2004 Elsevier Inc. All rights reserved.
dc.fechaingreso.objetodigital17-04-2024
dc.format.extent17 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.jmva.2004.11.002
dc.identifier.issn0047-259X
dc.identifier.urihttps://doi.org/10.1016/j.jmva.2004.11.002
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/76410
dc.identifier.wosidWOS:000232730600003
dc.information.autorucMatemática;Arellano R;S/I;58107
dc.issue.numero2
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final281
dc.pagina.inicio265
dc.publisherELSEVIER INC
dc.revistaJOURNAL OF MULTIVARIATE ANALYSIS
dc.rightsacceso restringido
dc.subjectinvariance
dc.subjectmaximum likelihood
dc.subjectposterior distribution
dc.subjectprior distribution
dc.subjectstructural model
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleSkew normal measurement error models
dc.typeartículo
dc.volumen96
sipa.codpersvinculados58107
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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