DISCRETIZATION OF THE METHOD OF GENERATING AN EXPANDED FAMILY OF DISTRIBUTIONS BASED UPON TRUNCATED DISTRIBUTIONS

Abstract

Discretization translates the continuous functions into discrete version making them more adaptable for numerical computation and application in applied mathematics and computer sciences. In this article, discrete analogues of a generalization method of generating a new family of distributions is provided. Several new discrete distributions are derived using the proposed methodology. A discrete Weibull-Geometric distribution is considered and various of its significant characteristics including moment, survival function, reliability function, quantile function, and order statistics are discussed. The method of maximum likelihood and the method of moments are used to estimate the model parameters. The performance o f the proposed model is probed through a real data set. A comparison of our model with some existing models is also given to demonstrate its efficiency.