Please use this identifier to cite or link to this item:
Type: Artigo de periódico
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: Skew-t distribution
Gibbs algorithm
Multivariate null intercepts model
Measurement error
Country: Estados Unidos
Rights: fechado
Identifier DOI: 10.1007/s00362-008-0138-z
Date Issue: 2010
Appears in Collections:IMECC - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
art_LACHOS_Bayesian_analysis_of_skew-t_multivariate_null_intercept_2010.pdfpublished version255.32 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.