multivariate restricted skew-normal scale mixtureof birnbaum-saunders distribution

In spite of widespread use as well as theoretical properties of the multivariate scale mixture of normal distributions, practical studies show a lack of stability and robustness against asymmetric features such as asymmetry and heavy tails. in this paper, we develop a new multivariate model by assuming the birnbaum-saunders distribution for the mixing variable in the scale mixture of the restricted skew-normal distribution. an analytically simple and efficient em-type algorithm is adopted for iteratively computing maximum likelihood estimate of model parameters. to account standard errors, the observed in-formation matrix is derived analytically by offering an information-based ap-proach. results obtained from real and simulated datasets are reported to illustrate the practical utility of the proposed methodology.