Scale mixtures of multivariate centered skew-normal distributions

The most popular approach for modeling multivariate data in many research areas is based on the multivariate normal distribution. However, this approach may not be suitable when dealing with data presenting skewness and/or heavy tail distribution. Thus, the scale mixtures of multivariate skew-normal distributions become an alternative distribution to deal with this scenario. In this context, we introduce the scale mixtures of multivariate centered skew-normal (MCSN) distributions to circumvent some inferential and interpretation problems. Some related properties of this family and Bayesian inference are presented. A Monte Carlo simulation study is carried out to evaluate the parameter recovery. The methodology is illustrated by analyzing a real data set where the new distributions outperform the MCSN distribution.