Bayesian analysis of skew-t multivariate null intercept measurement error model

被引：5

作者：

Lachos, Victor H. ^{[2
]}

Cancho, Vicente G. ^{[1
]}

Aoki, Reiko ^{[1
]}

机构：

[1] Univ Sao Paulo, ICMC, Dept Matemat Aplicada & Estat, BR-13560970 Sao Paulo, Brazil

[2] Univ Estadual Campinas, IMECC, Dept Estat, BR-13083859 Sao Paulo, Brazil

来源：

STATISTICAL PAPERS | 2010年 / 51卷 / 03期

基金：

巴西圣保罗研究基金会;

关键词：

Skew-t distribution; Gibbs algorithm; Metropolis-Hasting; Skewness; Multivariate null intercepts model; Measurement error; MAXIMUM LIKELIHOOD ESTIMATION; DISTRIBUTIONS;

D O I：

10.1007/s00362-008-0138-z

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：531 / 545

页数：15

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