A multivariate model for discrete data sets

Abstract

Many authors have suggested different methods for constructing meaningful multivariate discrete distributions Kemp and Papageorgiu (1982), Marshall and Olkin (1985). There are some drawbacks to the existing multivariate families because of their restricted covariation patterns Taillie et al. (1979). In this paper is proposed a new statistical model, which will allow more flexibility and will not be constrained by the creation of a bivariate or multivariate version of a specific univariate distribution. The method consists of constructing trivariate models using the following three concepts: the ascending diagonal arrays, the third marginal distribution and the total of variables distribution. The multivariate case will be further derived by a reduction to a number of trivariate models.