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This study explores a Gaussian quasi-likelihood approach for estimating parameters of diffusion processes with Markovian regime switching. Assuming the ergodicity under high-frequency sampling, we will show the asymptotic normality of the…

Statistics Theory · Mathematics 2025-05-19 Yuzhong Cheng , Hiroki Masuda

We study continuous time Markov processes on graphs. The notion of frequency is introduced, which serves well as a scaling factor between any Markov time of a continuous time Markov process and that of its jump chain. As an application, we…

Probability · Mathematics 2007-05-23 Jianjun Tian , Xiao-Song Lin

We investigate the use of discrete-time quantum walks to sample from an almost-uniform distribution, in the absence of any external source of randomness. Integers are encoded on the vertices of a cycle graph, and a quantum walker evolves…

Quantum Physics · Physics 2025-11-12 Marco Radaelli , Claudia Benedetti , Stefano Olivares

In random walks, the path representation of the Green's function is an infinite sum over the length of path probability density functions (PDFs). Here we derive and solve, in Laplace space, the recursion relation for the n order path PDF…

Mathematical Physics · Physics 2019-08-19 O. Flomenbom , R. J. Silbey

We consider stochastic processes on complete, locally compact tree-like metric spaces $(T,r)$ on their "natural scale" with boundedly finite speed measure $\nu$. Given a triple $(T,r,\nu)$ such a speed-$\nu$ motion on $(T,r)$ can be…

Probability · Mathematics 2017-04-04 Siva Athreya , Wolfgang Löhr , Anita Winter

Continuous time random walks (CTRWs) are versatile models for anomalous diffusion processes that have found widespread application in the quantitative sciences. Their scaling limits are typically non-Markovian, and the computation of their…

Probability · Mathematics 2014-07-25 Mark M. Meerschaert , Peter Straka

In the first part of this thesis, we study a Markov chain on $\mathbb{R}_+ \times S$, where $\mathbb{R}_+$ is the non-negative real numbers and $S$ is a finite set, in which when the $\mathbb{R}_+$-coordinate is large, the $S$-coordinate of…

Probability · Mathematics 2018-02-20 Chak Hei Lo

Let (S(t)) be a one-parameter family S = (S(t)) of positive integral operators on a locally compact space L. For a possibly non-uniform partition of [0,1] define a measure on the path space C([0,1],L) by using a) S(dt) for the transition…

Probability · Mathematics 2007-05-23 O. G. Smolyanov , H. v. Weizsaecker , O. Wittich

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a time and path-dependent…

Probability · Mathematics 2023-11-07 David Criens , Lars Niemann

Given random walk on a graph, the corresponding discrete-time quantum walk can be constructed using the method proposed by Szegedy. On the other hand, given a partition of the set of states of a Markov chain, one can study the corresponding…

Quantum Physics · Physics 2026-03-17 Adam Doliwa , Artur Siemaszko , Adam Zalewski

We extend the Ruzhansky-Turunen theory of pseudo differential operators on compact Lie groups into a tool that can be used to investigate group-valued Markov processes in the spirit of the work in Euclidean spaces of N.Jacob and…

Probability · Mathematics 2011-01-27 David Applebaum

The literature on Bayesian methods for the analysis of discrete-time semi-Markov processes is sparse. In this paper, we introduce the semi-Markov beta-Stacy process, a stochastic process useful for the Bayesian non-parametric analysis of…

Statistics Theory · Mathematics 2020-07-24 Andrea Arfè , Stefano Peluso , Pietro Muliere

In this paper, we study nonlocal random walk strategies generated with the fractional Laplacian matrix of directed networks. We present a general approach to analyzing these strategies by defining the dynamics as a discrete-time Markovian…

Statistical Mechanics · Physics 2020-09-02 A. P. Riascos , T. M. Michelitsch , A. Pizarro-Medina

This paper presents a nonparametric method for estimating the conditional density associated to the jump rate of a piecewise-deterministic Markov process. In our framework, the estimation needs only one observation of the process within a…

Statistics Theory · Mathematics 2012-07-12 Romain Azaïs , François Dufour , Anne Gégout-Petit

We consider the problem of stochastic flow of multiple particles traveling on a closed loop, with a constraint that particles move without passing. We use a Markov chain description that reduces the problem to a generalized random walk on a…

Probability · Mathematics 2007-05-23 J. D. Skufca

The planar symmetric Markov random flight $\bold X(t), \; t>0,$ is represented by the stochastic motion of a particle moving with constant finite speed $c>0$ in the Euclidean plane $\Bbb R^2$ and taking on its initial and each new…

Probability · Mathematics 2025-07-11 Alexander D. Kolesnik

We consider a class of discrete $q$-state spin models defined in terms of a translation-invariant quasilocal specification with discrete clock-rotation invariance which have extremal Gibbs measures $\mu'_{\varphi}$ labeled by the…

Probability · Mathematics 2014-09-15 Benedikt Jahnel , Christof Külske

This paper studies long range random walks on ${\mathbb{Z}_q}^d$. $X_{t+1} = X_t + Z_t \mod q$, with $(Z_t)$ independent and identically distributed. Multiple entries of $Z_t$ can be non-zero in a transition. An emphasis is on finding the…

Probability · Mathematics 2025-10-28 Robert Griffiths , Shuhei Mano

We study a model of active particles that perform a simple random walk and on top of that have a preferred direction determined by an internal state which is modelled by a stationary Markov process. First we calculate the limiting diffusion…

Probability · Mathematics 2021-06-30 Bart van Ginkel , Bart van Gisbergen , Frank Redig

This paper is devoted to the analysis of the finite-dimensional distributions and asymptotic behavior of extremal Markov processes connected to the Kendall convolution. In particular, based on its stochastic representation, we provide…

Probability · Mathematics 2019-10-10 Marek Arendarczyk , Barbara Jasiulis-Gołdyn , Edward Omey