  The Birnbaum-Saunders distribution has been widely applied in several areas
of science and although several methodologies related to this distribution have
been proposed, the problem of determining the optimal sample size for
estimating its mean has not yet been studied. For this purpose, we propose a
methodology to determine the optimal sample size under a decision-theoretic
approach. In this approach, we consider loss functions for point and interval
inference. Finally, computational tools in the R language were developed to use
in practice.
