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The local time in an ensemble of particles measures the amount of time the particles spend in the vicinity of a given point in space. Here we study fluctuations of the empirical time average $R= T^{-1}\int_{0}^{T}\rho\left(x=0,t\right)\,dt$…

Statistical Mechanics · Physics 2024-03-18 Naftali R. Smith , Baruch Meerson

We investigate the problem of quantifying contraction coefficients of Markov transition kernels in Kantorovich ($L^1$ Wasserstein) distances. For diffusion processes, relatively precise quantitative bounds on contraction rates have recently…

Probability · Mathematics 2018-08-22 Andreas Eberle , Mateusz B. Majka

Motivated by robotic surveillance applications, this paper studies the novel problem of maximizing the return time entropy of a Markov chain, subject to a graph topology with travel times and stationary distribution. The return time entropy…

Optimization and Control · Mathematics 2018-05-29 Xiaoming Duan , Mishel George , Francesco Bullo

We establish the consistency of a local time approximation of a diffusion at a sticky threshold based on high-frequency observations. First, we prove the result for sticky Brownian motion, and then extend it to It\^o diffusions with a…

Probability · Mathematics 2024-11-08 Alexis Anagnostakis

We provide a general framework for computing upper bounds on mixing times of finite Markov chains when its minimal ideal is left zero. Our analysis is based on combining results by Brown and Diaconis with our previous work on stationary…

Probability · Mathematics 2023-01-04 John Rhodes , Anne Schilling

In this paper we are concerned with hitting times of a family of density-dependent Markov chains. A moderate deviation principle of the hitting time is given. The proof of the main theorem relies heavily on moderate deviations of…

Probability · Mathematics 2022-06-15 Yuheng He , Xiaofeng Xue

We consider a Hidden Markov Model (HMM) where the integrated continuous-time Markov chain can be observed at discrete time points perturbed by a Brownian motion. The aim is to derive a filter for the underlying continuous-time Markov chain.…

Probability · Mathematics 2021-07-21 Nicole Bäuerle , Igor Gilitschenski , Uwe D. Hanebeck

By proving a local limit theorem for higher-order transitions, we determine the time required for necklace chains to be close to stationarity. Because necklace chains, built by arranging identical smaller chains around a directed cycle, are…

Probability · Mathematics 2021-11-22 Elizabeth L. Wilmer

We study the problem of characterizing the expected hitting times for a robust generalization of continuous-time Markov chains. This generalization is based on the theory of imprecise probabilities, and the models with which we work…

Probability · Mathematics 2022-06-28 Thomas Krak

We revisit the classical problem of approximating a stochastic differential equation by a discrete-time and discrete-space Markov chain. Our construction iterates Caratheodory's theorem over time to match the moments of the increments…

Probability · Mathematics 2021-11-08 Francesco Cosentino , Harald Oberhauser , Alessandro Abate

We consider Markov chains on general state spaces in stationary random environment which are defined by a random mapping that is contractive up to a bounded perturbation. We prove their convergence to a limiting law, providing convergence…

Probability · Mathematics 2025-12-18 Attila Lovas , Miklós Rásonyi , Lionel Truquet

In [4], we examined the use of coupling to obtain bounds on the mixing time of statistics on Markov chains. In the present paper, we consider the same general problem, but using strong stationary times rather than coupling. We discuss…

Probability · Mathematics 2019-10-10 Graham White

We consider the model of Brownian motion indexed by the Brownian tree, which has appeared in a variety of different contexts in probability, statistical physics and combinatorics. For this model, the total occupation measure is known to…

Probability · Mathematics 2023-06-16 Jean-François Le Gall

Let X_{n} be an integer valued Markov Chain with finite state space. Let S_{n}=\sum_{k=0}^{n}X_{k} and let L_{n}(x) be the number of times S_{k} hits x up to step n. Define the normalized local time process t_{n}(x) by…

Probability · Mathematics 2012-09-25 Michael Bromberg , Zemer Kosloff

We study inhomogeneous continuous-time weakly ergodic Markov chains with a finite state space. We introduce the notion of a Markov chain with the regular structure of an infinitesimal matrix and study the sharp upper bounds on the rate of…

Probability · Mathematics 2020-02-17 A. I. Zeifman , Y. A. Satin , K. M. Kiseleva

Consider a discrete time, ergodic Markov chain with finite state space which is started from stationarity. Fill and Lyzinski (2014) showed that, in some cases, the hitting time for a given state may be represented as a sum of a geometric…

Probability · Mathematics 2018-12-20 Fraser Daly

We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random walk on a regular Markov chain and a Hermitian matrix-valued…

Machine Learning · Statistics 2020-10-30 Jiezhong Qiu , Chi Wang , Ben Liao , Richard Peng , Jie Tang

We introduce a discrete-time random walk model on a one-dimensional lattice with a nonconstant sojourn time and prove that the discrete density converges to a solution of a continuum diffusion equation. Our random walk model is not…

Analysis of PDEs · Mathematics 2023-02-14 Jaywan Chung , Yong-Jung Kim , Min-Gi Lee

We investigate multivariate regular variation in the context of time-homogeneous Markov chains on general vector spaces and in random coefficient linear models. In the first part, we show that the regular variation of the stationary…

Probability · Mathematics 2025-10-23 Piotr Dyszewski , Tamara Mika

We study the ergodic behaviour of a discrete-time process $X$ which is a Markov chain in a stationary random environment. The laws of $X_t$ are shown to converge to a limiting law in (weighted) total variation distance as $t\to\infty$.…

Probability · Mathematics 2019-07-29 Balazs Gerencser , Miklos Rasonyi