2014/06/01 by Arellano-Valle, Reinaldo B., Contreras-Reyes, Javier E.
#62Hxx #Computation (stat.CO) #FOS: Computer and information sciences #Methodology (stat.ME)
paper · doi:10.48550/arxiv.1406.0182
The assumption of normality in data has been considered in the field of statistical analysis for a long time. However, in many practical situations, this assumption is clearly unrealistic. It has recently been suggested that the use of distributions indexed by skewness/shape parameters produce more exibility in the modelling of different applications. Consequently, the results show a more realistic interpretation for these problems. For these reasons, the aim of this paper is to investigate the effects of the generalisation of a discrimination function method through the class of multivariate extended skew-elliptical distributions, study in detail the multivariate extended skew-normal case and develop a quadratic approximation function for this family of distributions. A simulation study is reported to evaluate the adequacy of the proposed classification rule as well as the performance of the EM algorithm to estimate the model parameters.