Skew-normal linear calibration: a Bayesian perspective
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
|---|---|
| Data(s) |
20/10/2012
20/10/2012
2008
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| Resumo |
In this paper, we present a Bayesian approach for estimation in the skew-normal calibration model, as well as the conditional posterior distributions which are useful for implementing the Gibbs sampler. Data transformation is thus avoided by using the methodology proposed. Model fitting is implemented by proposing the asymmetric deviance information criterion, ADIC, a modification of the ordinary DIC. We also report an application of the model studied by using a real data set, related to the relationship between the resistance and the elasticity of a sample of concrete beams. Copyright (C) 2008 John Wiley & Sons, Ltd. Brazilian Agency Brazilian Agency Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) CNPq |
| Identificador |
JOURNAL OF CHEMOMETRICS, v.22, n.7/Ago, p.472-480, 2008 0886-9383 http://producao.usp.br/handle/BDPI/30531 10.1002/cem.1178 |
| Idioma(s) |
eng |
| Publicador |
WILEY-BLACKWELL |
| Relação |
Journal of Chemometrics |
| Direitos |
restrictedAccess Copyright WILEY-BLACKWELL |
| Palavras-Chave | #Gibbs sampler #skewness #skew-normal distribution #hierarchical model #DISTRIBUTIONS #Automation & Control Systems #Chemistry, Analytical #Computer Science, Artificial Intelligence #Instruments & Instrumentation #Mathematics, Interdisciplinary Applications #Statistics & Probability |
| Tipo |
article original article publishedVersion |
