A New Fractional Poisson Process Governed by a Recursive Fractional Differential Equation

Zhehao Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper proposes a new fractional Poisson process through a recursive fractional differential governing equation. Unlike the homogeneous Poison process, the Caputo derivative on the probability distribution of k jumps with respect to time is linked to all probability distribution functions of j jumps, where j is a non-negative integer less than or equal to k. The distribution functions of arrival times are derived, while the inter-arrival times are no longer independent and identically distributed. Further, this new fractional Poisson process can be interpreted as a homogeneous Poisson process whose natural time flow has been randomized, and the underlying time randomizing process has been studied. Finally, the conditional distribution of the kth order statistic from random number samples, counted by this fractional Poisson process, is also discussed.

Original languageEnglish
Article number418
JournalFractal and Fractional
Volume6
Issue number8
DOIs
Publication statusPublished - Aug 2022

Keywords

  • Fox H function
  • Lamperti law
  • Mittag–Leffler functions
  • fractional differential equations
  • order statistic
  • subordinator and inverse stable subordinator

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