Generalized Counting Process: its Non-Homogeneous and Time-Changed Versions
K. K. Kataria, M. Khandakar, P. Vellaisamy

TL;DR
This paper introduces non-homogeneous and fractional versions of the generalized counting process, deriving their governing equations, distributions, and properties, with applications to ruin theory and order statistics.
Contribution
It develops a comprehensive framework for non-homogeneous and fractional generalized counting processes, including their governing equations, distributions, and applications, extending prior homogeneous models.
Findings
Derived differential-integral equations for marginal distributions.
Obtained distributions of first passage times and order statistics.
Established long-range dependence properties of the fractional process.
Abstract
We introduce a non-homogeneous version of the generalized counting process (GCP), namely, the non-homogeneous generalized counting process (NGCP). We time-change the NGCP by an independent inverse stable subordinator to obtain its fractional version, and call it as the non-homogeneous generalized fractional counting process (NGFCP). A generalization of the NGFCP is obtained by time-changing the NGCP with an independent inverse subordinator. We derive the system of governing differential-integral equations for the marginal distributions of the increments of NGCP, NGFCP and its generalization. Then, we consider the GCP time-changed by a multistable subordinator and obtain its L\'evy measure, associated Bern\v{s}tein function and distribution of the first passage times. The GCP and its fractional version, that is, the generalized fractional counting process when time-changed by a L\'evy…
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Taxonomy
TopicsStatistical Distribution Estimation and Applications · Bayesian Methods and Mixture Models · Probability and Risk Models
