Abstract
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.
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Cancho, V.G., Lachos, V.H. & Ortega, E.M.M. A nonlinear regression model with skew-normal errors. Stat Papers 51, 547–558 (2010). https://doi.org/10.1007/s00362-008-0139-y
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DOI: https://doi.org/10.1007/s00362-008-0139-y