  In this paper, an alternative Discrete skew Logistic distribution is
proposed, which is derived by using the general approach of discretizing a
continuous distribution while retaining its survival function. The properties
of the distribution are explored and it is compared to a discrete distribution
defined on integers recently proposed in the literature. The estimation of its
parameters are discussed, with particular focus on the maximum likelihood
method and the method of proportion, which is particularly suitable for such a
discrete model. A Monte Carlo simulation study is carried out to assess the
statistical properties of these inferential techniques. Application of the
proposed model to a real life data is given as well.
