2025-03-142025-03-14REVSTAT-Statistical Journal, 21(1), 1–20.https://hdl.handle.net/20.500.12740/17351It is well known that it is possible to represent a Birnbaum-Saunders variable as a relatively simple (and invertible) function of a standard normal random variable. Marginal transformations of this kind are applied in this paper to a bivariate distribution with generalized skew-normal conditionals (and normal marginals), to obtain a new bivariate Birnbaum-Saunders distribution. Parameter estimation for this model is implemented using an EM algorithm. A simulation study sheds light on the performance of the estimation strategy. Data from a cancer risk study is used to illustrate use of the model. For this data set, the new model exhibits better performance than does a competing skew-normal based model already discussed in the literature. Possible multivariate extensions of the new model are outlined.Birnbaum-Saunders distributionbivariate distributionconditional specificationsEM algorithmArtículohttps://doi.org/10.57805/revstat.v21i1.396