Lunch Seminar MESIO UPC-UB

Speaker:  Marta Perez-Casany
                Department of Statistics and Operations Research, UPC

Title:    The Marshall-Olkin transformation Applied to count probability distributions

Abstract:
In 1997, Marshall and Olkin defined  a way of generalizing a family of probability distributions by increasing its number of parameters by one. This mechanism has been used quite a lot to generalize continuous probability distributions, but very few research has been done with respect to the discrete case.

The talk has three parts. In the first one the Marshall-Olkin transformation is defined and some of the main properties derived from applying it to the discrete case are presented. The second part is devoted to the Mashall-Olkin Extended Zipf distribution and its application in social networking. Finally, in the third part a natural way of generalizing the Marshall-Olkin transformation is presented.