A Continuous Analog of the Generalized Hypergeometric Distribution Generated by Dediscretization Method

Abstract

In this paper, we shall attempt to introduce a new continuous analog of the regularly varying generalized hypergeometric distribution by the dediscretization method. The density, cumulative distribution, survival and hazard rate functions are obtained for the model. The density, cumulative distribution and hazard rate functions are illustrated by some figures. With the help of Monte Carlo method, simulation studies are done to obtain biases and mean square errors of the maximum likelihood estimations for the model’s unknown parameters. We see that our simulation method has satisfactory results.