Description: During the last decade, a vast activity had been observed in generalizing of the classical discrete distributions. The main idea was to apply the extended versions fur modeling different kinds of dependent count or frequency data structure in various fields. In the present paper we suggest extensions of the classical univariate geometric, negative binomial, Poisson, Bernoulli, binomial and logarithmic series distributions, by including an additional parameter. It has a natural interpretation in terms of zero-inflation, and because of this we named the corresponding generalized versions adding inflated-parameter.

Description: View the ARCH Table of Contents 2020.2.

Description: This is a listing of the participants for the 41st Actuarial Research Conference.

Description: View information about the 2019.1 Actuarial Research Conference Proceedings.

Description: This is article identifies and quantifies how one of several prospective cures for chronic conditions will impact healthcare.

Description: This poster describes the optimal investment and benefit payment problem for a target benefit pension with default risk and model uncertainty.

Description: Genetic algorithms [GAs] and neural networks [NNs] are currently being used in actuarial and financial modeling. Nonetheless, while there is a general awareness of the nature of these techniques, there is often only vague familiarity with the details of how they are implemented. This paper is intended to help alleviate this situation. Its purpose is to present an overview of GAs and NNs, which includes an explanation of what they are, how they work, and an example of how they are implemented.