  The Birnbaum-Saunders distribution is a flexible and useful model which has
been used in several fields. In this paper, a new bimodal version of this
distribution based on the alpha-skew-normal distribution is established. We
discuss some of its mathematical and inferential properties. We consider
likelihood-based methods to estimate the model parameters. We carry out a Monte
Carlo simulation study to evaluate the performance of the maximum likelihood
estimators. For illustrative purposes, three real data sets are analyzed. The
results indicated that the proposed model outperformed some existing models in
the literature, in special, a recent bimodal extension of the Birnbaum-Saunders
distribution.
