Fractional Poisson Random Fields on $\mathbb{R}^2_+$

TL;DR

This paper introduces a fractional Poisson random field on positive planes, explores its properties, representations, and generalizations, and applies it to particle motion and compound fields, advancing stochastic process theory.

Contribution

It presents a new fractional Poisson random field, its representations, generalizations to higher dimensions, and applications to particle motion and compound processes, with explicit probability mass functions.

Findings

Closed-form probability mass function via Wright function

Time-changed representations for GPP and FPRF

Generalized Poisson random field on $ ^d_+$

Abstract

In this paper, we consider a fractional Poisson random field (FPRF) on positive plane. It is defined as a process whose one dimensional distribution is the solution of a system of fractional partial differential equations. A time-changed representation for the FPRF is given in terms of the composition of Poisson random field with a bivariate random process. Some integrals of the FPRF are introduced and studied. Using the Adomian decomposition method, a closed form expression for its probability mass function is obtained in terms of the generalized Wright function. Some results related to the order statistics of random numbers of random variables are presented. Also, we introduce a generalization of Poisson random field on $\mathbb{R}^d_+$, $d\ge1$ which reduces to the Poisson random field in a special case. For $d=1$, it further reduces to a generalized Poisson process (GPP). A time-changed representation for the GPP is established. Moreover, we construct a time-changed linear and planer random motions of a particle driven by the GPP. The conditional distribution of the random position of particle is derived. Later, we define the compound fractional Poisson random field via FPRF. Also, a generalized version of it on $\mathbb{R}^d_+$, $d\ge1$ is discussed.