A PROBABILISTIC PROGRAMMING TECHNIQUE FOR BIVARIATE LOMAX RANDOM PARAMETERS
Rasha Ebaid, Afaf El-Dash · Far East Journal of Mathematical Sciences (FJMS) · 2021
In this paper, we consider a probabilistic programming technique with dividual and individual constraints, where the right-hand side (RHS) parameters follow the marginal Lomax (Pareto type II) distribution, and a new bivariate Lomax distribution, respectively. Properties of the new bivariate distribution are discussed. We show how the chance-constraints are transformed into equivalent deterministic linear constraints that can be solved using Simplex method. Finally, a numerical example is given to illustrate the transformation and solution process of the probabilistic model.