Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/348321
Type: Artigo
Title: Bayesian analysis of skew-t multivariate null intercept measurement error model
Author: Lachos, Victor H.
Cancho, Vicente G.
Aoki, Reiko
Abstract: The multivariate skew-t distribution (J Multivar Anal 79:93–113, 2001; J R Stat Soc, Ser B 65:367–389, 2003; Statistics 37:359–363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew–normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763–771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry
Subject: Algoritmo de Gibbs
Country: Alemanha
Editor: Springer
Rights: Fechado
Identifier DOI: 10.1007/s00362-008-0138-z
Address: https://link.springer.com/article/10.1007%2Fs00362-008-0138-z
Date Issue: 2010
Appears in Collections:IMECC - Artigos e Outros Documentos

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