  The use of continuous probability distributions has been widespread in
problems with purely discrete nature. In general, such distributions are not
appropriate in this scenario. In this paper, we introduce a class of discrete
and asymmetric distributions based on the family of continuous log-symmetric
distributions. Some properties are discussed as well as estimation by the
maximum likelihood method. A Monte Carlo simulation study is carried out to
evaluate the performance of the estimators, and censored and uncensored data
sets are used to illustrate the proposed methodology.
