A nonlinear regression model with skew-normal errors


Autoria(s): CANCHO, Vicente G.; LACHOS, Victor H.; ORTEGA, Edwin M. M.
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

http://dx.doi.org/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