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Related papers: Fractional non-homogeneous counting process

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A non-Markovian counting process, the `generalized fractional Poisson process' (GFPP) introduced by Cahoy and Polito in 2013 is analyzed. The GFPP contains two index parameters $0<\beta\leq 1$, $\alpha >0$ and a time scale parameter.…

Statistical Mechanics · Physics 2020-04-22 Thomas M. Michelitsch , Alejandro P. Riascos

We introduce two non-homogeneous processes: a fractional non-homogeneous Poisson process of order $k$ and and a fractional non-homogeneous P\'olya-Aeppli process of order $k$. We characterize these processes by deriving their non-local…

Probability · Mathematics 2021-05-04 Tetyana Kadankova , Nikolai Leonenko , Enrico Scalas

We present new properties for the Fractional Poisson process and the Fractional Poisson field on the plane. A martingale characterization for Fractional Poisson processes is given. We extend this result to Fractional Poisson fields,…

Probability · Mathematics 2018-01-30 Giacomo Aletti , Nikolai Leonenko , Ely Merzbach

In this paper we present multivariate space-time fractional Poisson processes by considering common random time-changes of a (finite-dimensional) vector of independent classical (non-fractional) Poisson processes. In some cases we also…

Probability · Mathematics 2015-07-22 Luisa Beghin , Claudio Macci

We survey the 'generalized fractional Poisson process' (GFPP). The GFPP is a renewal process generalizing Laskin's fractional Poisson counting process and was first introduced by Cahoy and Polito. The GFPP contains two index parameters with…

Statistical Mechanics · Physics 2020-07-02 Thomas M. Michelitsch , Alejandro P. Riascos

Dynamical scaling is an asymptotic property typical for the dynamics of first-order phase transitions in physical systems and related to self-similarity. Based on the integral-representation for the marginal probabilities of a fractional…

Probability · Mathematics 2021-07-23 Markus Kreer

We define a novel class of time changed Pearson diffusions, termed stretched non local Pearson diffusions, where the stochastic time change model has the Kilbas Saigo function as its Laplace transform. Moreover, we introduce a stretched…

Probability · Mathematics 2025-05-13 Luisa Beghin , Nikolai Leonenko , Ivan Papić , Jayme Vaz

In this paper, we obtain additional results for a fractional counting process introduced and studied by Di Crescenzo et al. (2016). For convenience, we call it the generalized fractional counting process (GFCP). It is shown that the…

Probability · Mathematics 2023-02-15 K. K. Kataria , M. Khandakar

The Mittag-Leffler function $E_{\alpha}$ being a natural generalization of the exponential function, an infinite-dimensional version of the fractional Poisson measure would have a characteristic functional \[ C_{\alpha}(\phi)…

Probability · Mathematics 2010-02-11 Maria Joao Oliveira , Habib Ouerdiane , Jose Luis da Silva , R. Vilela Mendes

This paper studies the first hitting times of generalized Poisson processes $N^f(t)$, related to Bernstein functions $f$. For the space-fractional Poisson processes, $N^\alpha(t)$, $t>0$ (corresponding to $f= x^\alpha$), the hitting…

Probability · Mathematics 2016-04-19 R. Garra , E. Orsingher , M. Scavino

The space-fractional and the time-fractional Poisson processes are two well-known models of fractional evolution. They can be constructed as standard Poisson processes with the time variable replaced by a stable subordinator and its…

Probability · Mathematics 2016-08-09 Luisa Beghin , Costantino Ricciuti

This paper introduces the Generalized Space-Time Fractional Skellam Process (GSTFSP) and the Generalized Space Fractional Skellam Process (GSFSP). We investigate their distributional properties including the probability generating function…

Probability · Mathematics 2025-04-14 Kartik Tathe , Sayan Ghosh

We generate the fractional Poisson process by subordinating the standard Poisson process to the inverse stable subordinator. Our analysis is based on application of the Laplace transform with respect to both arguments of the evolving…

Probability · Mathematics 2013-05-24 Rudolf Gorenflo , Francesco Mainardi

Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has…

Statistical Mechanics · Physics 2009-11-18 Giulio Cottone , Mario Di Paola , Ralf Metzler

Within the framework of probability models for overdispersed count data, we propose the generalized fractional Poisson distribution (gfPd), which is a natural generalization of the fractional Poisson distribution (fPd), and the standard…

Probability · Mathematics 2021-01-12 Dexter Cahoy , Elvira Di Nardo , Federico Polito

Introducing the discrete probability distribution by means of the Prabhakar (or the three--parameter Mittag--Leffler) function, we establish explicit expressions for raw and factorial moments and also general fractional order moments.…

Classical Analysis and ODEs · Mathematics 2016-05-09 Tibor K. Pogány , Živorad Tomovski

We introduce a mltiparameter version of Skellam point process via multiparameter Poisson processes. Its distributional properties are studied in detail. Its compound representation is derived for a particular case. Also, its Riemann…

Probability · Mathematics 2025-09-17 Pradeep Vishwakarma

This paper combines probability theory and fractional calculus to derive a novel integral representation of the three-parameter Mittag-Leffler function or Prabhakar function, where the three parameters are combinations of four base…

Probability · Mathematics 2023-04-21 Nomvelo Karabo Sibisi

General fractional calculus offers an elegant and self-consistent path toward the generalization of fractional calculus to an enhanced class of kernels. Prabhakar's theory can be thought of, to some extent, as an explicit realization of…

Mathematical Physics · Physics 2019-11-25 Andrea Giusti

Random fields are useful mathematical tools for representing natural phenomena with complex dependence structures in space and/or time. In particular, the Gaussian random field is commonly used due to its attractive properties and…