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This paper presents a fractional generalized Cauchy process (FGCP) with an additive and a multiplicative Gaussian white noise for describing subordinated anomalous fluctuations. The FGCP displays intermittent dynamics during random time…

Statistical Mechanics · Physics 2019-03-27 Yusuke Uchiyama , Takanori Kadoya , Hidetoshi Konno

In this paper, we define a compound generalized fractional counting process (CGFCP) which is a generalization of the compound versions of several well-known fractional counting processes. We obtain its mean, variance, and the fractional…

Probability · Mathematics 2024-05-21 Ritik Soni , Ashok Kumar Pathak

In the context of time-subordinated Brownian motion models, Fourier theory and methodology are proposed to modelling the stochastic distribution of time increments. Gaussian Variance-Mean mixtures and time-subordinated models are reviewed…

Mathematical Finance · Quantitative Finance 2025-10-21 Rohan Shenoy , Peter Kempthorne

We study the order statistics of one dimensional branching Brownian motion in which particles either diffuse (with diffusion constant $D$), die (with rate $d$) or split into two particles (with rate $b$). At the critical point $b=d$ which…

Statistical Mechanics · Physics 2014-06-03 Kabir Ramola , Satya N. Majumdar , Gregory Schehr

In this paper, we introduce and study two time-changed variants of the generalized fractional Skellam process. These are obtained by time-changing the generalized fractional Skellam process with an independent L\'evy subordinator with…

Probability · Mathematics 2025-10-31 Mostafizar Khandakar , Bratati Pal , Palaniappan Vellaisamy

This paper introduces the Generalized Fractional Compound Poisson Process (GFCPP), which claims to be a unified fractional version of the compound Poisson process (CPP) that encompasses existing variations as special cases. We derive its…

Probability · Mathematics 2023-07-25 Neha Gupta , Aditya Maheshwari

Recently the so-called Prabhakar generalization of the fractional Poisson counting process attracted much interest for his flexibility to adapt real world situations. In this renewal process the waiting times between events are IID…

Probability · Mathematics 2020-12-10 Thomas M. Michelitsch , Federico Polito , Alejandro P. Riascos

We analyze here different types of fractional differential equations, under the assumption that their fractional order $\nu \in (0,1] $ is random\ with probability density $n(\nu).$ We start by considering the fractional extension of the…

Probability · Mathematics 2015-05-27 Luisa Beghin

We study a class of discrete-time random walks in $\mathbb{R}^d$ whose conditional drift decays polynomially in time and grows polynomially with the distance from the origin to the current position. This class is related to several models…

Probability · Mathematics 2026-05-19 Ngo P. N. Ngoc , Tuan-Minh Nguyen

Using the Feynman-Kac and Cameron-Martin-Girsanov formulas, we obtain a generalized integral fluctuation theorem (GIFT) for discrete jump processes by constructing a time-invariable inner product. The existing discrete IFTs can be derived…

Statistical Mechanics · Physics 2009-06-11 Fei Liu , Yu-Pin Luo , Ming-Chang Huang , Zhong-can Ou-Yang

Continuous time random walks impose a random waiting time before each particle jump. Scaling limits of heavy tailed continuous time random walks are governed by fractional evolution equations. Space-fractional derivatives describe heavy…

Probability · Mathematics 2009-06-25 Mark M. Meerschaert , Erkan Nane , Yimin Xiao

We construct a stochastic process whose drift is a function of the process's local time at a reflecting barrier. The process arose as a model of the interactions of a Brownian particle and an inert particle in (Knight, 2001). Interesting…

Probability · Mathematics 2007-05-23 David White

In this note, by an elementary use of Girsanov's transform we show that the exit time for either a biased random walk or a drifted Brownian motion on a symmetric interval is stochastically monotone with respect to the drift parameter. In…

Probability · Mathematics 2025-06-05 Xi Geng , Greg Markowsky

We consider randomized computation of continuous data in the sense of Computable Analysis. Our first contribution formally confirms that it is no loss of generality to take as sample space the Cantor space of infinite FAIR coin flips. This…

Numerical Analysis · Mathematics 2019-06-18 Willem Fouché , Hyunwoo Lee , Donghyun Lim , Sewon Park , Matthias Schröder , Martin Ziegler

We study the connection between PDEs and L\'{e}vy processes running with clocks given by time-changed Poisson processes with stochastic drifts. The random times we deal with are therefore given by time-changed Poissonian jumps related to…

Probability · Mathematics 2014-01-15 Luisa Beghin , Mirko D'Ovidio

This paper studies a problem of Bayesian parameter estimation for a sequence of scaled counting processes whose weak limit is a Brownian motion with an unknown drift. The main result of the paper is that the limit of the posterior…

Statistics Theory · Mathematics 2015-03-19 Asaf Cohen

A compound Poisson process whose randomized time is an independent Poisson process is called compound Poisson process with Poisson subordinator. We provide its probability distribution, which is expressed in terms of the Bell polynomials,…

Probability · Mathematics 2015-11-18 Antonio Di Crescenzo , Barbara Martinucci , Shelemyahu Zacks

For a random walk defined for a doubly infinite sequence of times, we let the time parameter itself be an integer-valued process, and call the orginal process a random walk at random time. We find the scaling limit which generalizes the…

Probability · Mathematics 2013-07-30 Paul Jung , Greg Markowsky

We study a classical Bayesian statistics problem of sequentially testing the sign of the drift of an arithmetic Brownian motion with the $0$-$1$ loss function and a constant cost of observation per unit of time for general prior…

Probability · Mathematics 2015-09-03 Erik Ekström , Juozas Vaicenavicius

We consider continuous-time Markov chains on integers which allow transitions to adjacent states only, with alternating rates. We give explicit formulas for probability generating functions, and also for means, variances and state…

Probability · Mathematics 2019-10-30 Luisa Beghin , Claudio Macci , Barbara Martinucci