A nonlinear regression model with skew-normal errors
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
---|---|
Data(s) |
20/10/2012
20/10/2012
2010
|
Resumo |
In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129-150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171-178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality. FAPESP/FAEPEX-UNICAMP, Brazil Fundo de Apoio ao Ensino, à Pesquisa e Extensão - FAEPEX-UNICAMP Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) |
Identificador |
STATISTICAL PAPERS, v.51, n.3, p.547-558, 2010 0932-5026 http://producao.usp.br/handle/BDPI/28910 10.1007/s00362-008-0139-y |
Idioma(s) |
eng |
Publicador |
SPRINGER |
Relação |
Statistical Papers |
Direitos |
restrictedAccess Copyright SPRINGER |
Palavras-Chave | #Skew-normal distribution #EM-algorithm #Nonlinear regression models #MCMC #DISTRIBUTIONS #INFERENCE #Statistics & Probability |
Tipo |
article original article publishedVersion |