On a Multivariate Generalized Polya Process Without Regularity Property

Abstract

Most of the multivariate counting processes studied in the literature are regular processes, which implies, ignoring the types of the events, the non-occurrence of multiple events. However, in practice, several different types of events may occur simultaneously. In this paper, a new class of multivariate counting processes which allow simultaneous occurrences of multiple types of events is suggested and its stochastic properties are studied. For the modeling of such kind of process, we rely on the tool of superposition of seed counting processes. It will be shown that the stochastic properties of the proposed class of multivariate counting processes are explicitly expressed. Furthermore, the marginal processes are also explicitly obtained. We analyze the multivariate dependence structure of the proposed class of counting processes.

A Preventive Replacement Policy for a System Subject to Bivariate Generalized Polya Failure Process

“…[17] suggested a general theoretical framework for the multivariate counting process. Recently, new classes of multivariate counting processes have been developed in the literature (see [19][20][21]). Specifically, in [20], the multivariate generalized Polya process (MVGPP) with mathematically tractable properties was defined.…”