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We developed analytical and numerical methods to study a transport of non-interacting particles in large networks consisting of M d-dimensional containers C_1,...,C_M with radii R_i linked together by tubes of length l_{ij} and radii a_{ij}…

Statistical Mechanics · Physics 2009-11-11 L. Lizana , Z. Konkoli

A discrete-time Markov chain can be transformed into a new Markov chain by looking at its states along iterations of an almost surely finite stopping time. By the optional stopping theorem, any bounded harmonic function with respect to the…

Probability · Mathematics 2022-05-04 Iddo Ben-Ari , Behrang Forghani

Markov chains are a convenient means of generating realizations of networks, since they require little more than a procedure for rewiring edges. If a rewiring procedure exists for generating new graphs with specified statistical properties,…

Social and Information Networks · Computer Science 2012-02-17 Jaideep Ray , Ali Pinar , C. Seshadhri

The analysis of many problems of interest associated with Markov chains, e.g. stationary distributions, moments of first passage time distributions and moments of occupation time random variables, involves the solution of a system of linear…

Probability · Mathematics 2012-08-29 Jeffrey J. Hunter

In this work, we consider a finite-state inhomogeneous-time Markov chain whose probabilities of transition from one state to another tend to decrease over time. This can be seen as a cooling of the dynamics of an underlying Markov chain. We…

Probability · Mathematics 2017-05-08 Florian Bouguet , Bertrand Cloez

We provide explicit expressions for the constants involved in the characterisation of ergodicity of sub-geometric Markov chains. The constants are determined in terms of those appearing in the assumed drift and one-step minorisation…

Probability · Mathematics 2014-03-18 Christophe Andrieu , Gersende Fort , Matti Vihola

We propose a method to approximate continuous-time, continuous-state stochastic processes by a discrete-time Markov chain defined on a nonuniform grid. Our method provides exact moment matching for processes whose first and second moments…

Probability · Mathematics 2025-11-27 Do Hyun Kim , Ahmet Cetinkaya

We consider the problem of characterising expected hitting times and hitting probabilities for imprecise Markov chains. To this end, we consider three distinct ways in which imprecise Markov chains have been defined in the literature: as…

Probability · Mathematics 2020-01-28 Thomas Krak , Natan T'Joens , Jasper De Bock

This paper is concerned with ergodic properties of inhomogeneous Markov processes. Since the transition probabilities depend on initial times, the existing methods to obtain invariant measures for homogeneous Markov processes are not…

Probability · Mathematics 2025-01-24 Zhenxin Liu , Di Lu

There is a well-established theory linking certain semi-Markov chains and continuous-time random walks to time-fractional equations and anomalous diffusion. In this work, we go beyond the semi-Markov framework by considering some…

Probability · Mathematics 2026-02-27 Lorenzo Facciaroni , Costantino Ricciuti , Enrico Scalas

About two dozens of exactly solvable Markov chains on one-dimensional finite and semi-infinite integer lattices are constructed in terms of convolutions of orthogonality measures of the Krawtchouk, Hahn, Meixner, Charlier, $q$-Hahn,…

Probability · Mathematics 2022-06-17 Satoru Odake , Ryu Sasaki

In spatial statistics, kriging models are often designed using a stationary covariance structure; this translation-invariance produces models which have numerous favorable properties. This assumption can be limiting, though, in…

Computation · Statistics 2018-12-04 Michael McCourt , Gregory Fasshauer , David Kozak

Computational procedures for the stationary probability distribution, the group inverse of the Markovian kernel and the mean first passage times of an irreducible Markov chain, are developed using perturbations. The derivation of these…

Probability · Mathematics 2016-10-12 Jeffrey J. Hunter

Sewer pipe systems are essential for social and economic welfare. Managing these systems requires robust predictive models for degradation behaviour. This study focuses on probability-based approaches, particularly Markov chains, for their…

Methodology · Statistics 2024-07-18 Lisandro A. Jimenez-Roa , Tiedo Tinga , Tom Heskes , Marielle Stoelinga

We consider symmetric Markov chains on $\Bbb Z^d$ where we do {\bf not} assume that the conductance between two points must be zero if the points are far apart. Under a uniform second moment condition on the conductances, we obtain upper…

Probability · Mathematics 2007-05-23 Richard F. Bass , Takashi Kumagai

In this paper we consider the field of local times of a discrete-time Markov chain on a general state space, and obtain uniform (in time) upper bounds on the total variation distance between this field and the one of a sequence of $n$…

Probability · Mathematics 2019-03-25 Diego F. de Bernardini , Christophe Gallesco , Serguei Popov

Markov chains are convenient means of generating realizations of networks with a given (joint or otherwise) degree distribution, since they simply require a procedure for rewiring edges. The major challenge is to find the right number of…

Social and Information Networks · Computer Science 2012-11-01 J. Ray , A. Pinar , C. Seshadhri

We consider a time inhomogeneous strong Markov process $(\xi_t)_{t\ge 0}$ taking values in a Polish state space whose semigroup has a $T$-periodic structure. We give simple conditions which imply ergodicity of the grid chain…

Probability · Mathematics 2011-03-09 Reinhard Hoepfner , Eva Loecherbach

We consider continuous-space, discrete-time Markov chains on $\mathbb{R}^d$, that admit a finite number $N$ of metastable states. Our main motivation for investigating these processes is to analyse random Poincar\'e maps, which describe…

Probability · Mathematics 2025-08-19 Nils Berglund

For a Markov transition kernel $P$ and a probability distribution $ \mu$ on nonnegative integers, a time-sampled Markov chain evolves according to the transition kernel $P_{\mu} = \sum_k \mu(k)P^k.$ In this note we obtain CLT conditions for…

Probability · Mathematics 2011-06-07 Krzysztof Latuszynski , Gareth O. Roberts
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