  In this paper we introduce the zero-adjusted Birnbaum-Saunders regression
model. This new model generalizes at least seven Birnbaum-Saunders regression
models. The idea of this modeling is mixing a degenerate distribution at zero
with a Birnbaum-Saunders distribution. Besides the capacity to account for
excess zeros, the zero-adjusted Birnbaum-Saunders distribution additionally
produces an attractive modeling structure to right-skewed data. In this model,
the mean and precision parameter of the Birnbaum-Saunders distribution and the
probability of zeros can be related to linear and/or non-linear predictors
through link functions. We derive a type of residual to perform diagnostic
analysis and a perturbation scheme for identifying those observations that
exert unusual influence on the estimation process. Finally, two applications to
real data show the potential of the model.
