Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/348337
Type: Artigo
Title: Bayesian analysis for a skew extension of the multivariate null intercept measurement error model
Author: Cancho, V. G.
Aoki, Reiko
Lachos, V. H.
Abstract: Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leão Pinto Jr, Bayesian analysis of a multivariate null intercept error-in-variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763–771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161–178]
Subject: Distribuição normal assimétrica
Country: Reino Unido
Editor: Taylor & Francis
Rights: Fechado
Identifier DOI: 10.1080/02664760802319667
Address: https://www.tandfonline.com/doi/full/10.1080/02664760802319667
Date Issue: 2008
Appears in Collections:IMECC - Artigos e Outros Documentos

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