mixture of extended birnbaum-saunders distributions: an approach via the mean-mixture of normal models

The birnbaum-saunders (bs) distribution is one of the most considered right-skewed distributions to model failure times for materials subject to lifetime data. in this paper, a new extension of the bs model is initially proposed based on the family of mean-mixtures of normal distributions. then, we present a new probabilistic mixture model based on the new extended bs distribution for modeling and clustering right-skewed and heavy-tailed data. the maximum likelihood (ml) parameter estimates of the model in question are estimated by employing an expectation-maximization (em) type algorithm. moreover, the empirical information matrix is derived by using an information based approach. simulations and real data analysis illustrate the performance of the proposed methodology.