Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/55348
Type: Artigo
Title: Bayesian analysis of skew-normal independent linear mixed models with heterogeneity in the random-effects population
Author: Cabral, Celso Romulo Barbosa
Lachos, Victor Hugo
Madruga, Maria Regina
Abstract: We present a new class of models to fit longitudinal data, obtained with a suitable modification of the classical linear mixed-effects model. For each sample unit, the joint distribution of the random effect and the random error is a finite mixture of scale mixtures of multivariate skew-normal distributions. This extension allows us to model the data in a more flexible way, taking into account skewness, multimodality and discrepant observations at the same time. The scale mixtures of skew-normal form an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal, skew-Student-t, skew-slash and the skew-contaminated normal distributions as special cases, being a flexible alternative to the use of the corresponding symmetric distributions in this type of models. A simple efficient MCMC Gibbs-type algorithm for posterior Bayesian inference is employed. In order to illustrate the usefulness of the proposed methodology, two artificial and two real data sets are analyzed. (C) 2011 Elsevier B.V. All rights reserved.
We present a new class of models to fit longitudinal data, obtained with a suitable modification of the classical linear mixed-effects model. For each sample unit, the joint distribution of the random effect and the random error is a finite mixture of sca
Subject: Modelos lineares (Estatística)
Misturas finitas
Teoria bayesiana de decisão estatística
Métodos MCMC (Estatística)
Distribuição normal assimétrica
Country: Holanda
Editor: Elsevier
Citation: Journal Of Statistical Planning And Inference. Elsevier Science Bv, v. 142, n. 1, n. 181, n. 200, 2012.
Rights: fechado
Identifier DOI: 10.1016/j.jspi.2011.07.007
Address: https://www.sciencedirect.com/science/article/pii/S0378375811002771
Date Issue: 2012
Appears in Collections:IMECC - Artigos e Outros Documentos

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