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Let $(\xi_n)_{n=0}^\infty$ be a nonhomogeneous Markov chain taking values from finite state-space of $\mathbf{X}=\{1,2,\ldots,b\}$. In this paper, we will study the generalized entropy ergodic theorem with almost-everywhere and…

Probability · Mathematics 2015-01-19 Zhongzhi Wang , Weiguo Yang

In a highly influential paper, Bidigare, Hanlon and Rockmore showed that a number of popular Markov chains are random walks on the faces of a hyperplane arrangement. Their analysis of these Markov chains took advantage of the monoid…

Representation Theory · Mathematics 2012-09-19 Stuart Margolis , Franco Saliola , Benjamin Steinberg

We define an analog of Plancherel measure for the set of rooted unlabeled trees on n vertices, and a Markov chain which has this measure as its stationary distribution. Using the combinatorics of commutation relations, we show that order…

Combinatorics · Mathematics 2009-08-11 Jason Fulman

We consider refined versions of Markov chains related to juggling introduced by Warrington. We further generalize the construction to juggling with arbitrary heights as well as infinitely many balls, which are expressed more succinctly in…

Probability · Mathematics 2015-01-19 Arvind Ayyer , Jérémie Bouttier , Sylvie Corteel , François Nunzi

Knutson introduced two families of reverse juggling Markov chains (single and multispecies) motivated by the study of random semi-infinite matrices over $\mathbb{F}_q$. We present natural generalizations of both chains by placing generic…

Probability · Mathematics 2019-11-11 Arvind Ayyer , Svante Linusson

We introduce and study the permanence properties of the class of linear transfers between probability measures. This class contains all cost minimizing mass transports, but also martingale mass transports, the Schrodinger bridge associated…

Analysis of PDEs · Mathematics 2018-10-29 Malcolm Bowles , Nassif Ghoussoub

We study combinatorial inequalities for various classes of set systems: matroids, polymatroids, poset antimatroids, and interval greedoids. We prove log-concavity inequalities for counting certain weighted feasible words, which generalize…

Combinatorics · Mathematics 2024-08-01 Swee Hong Chan , Igor Pak

We develop a systematic matrix-analytic approach, based on intertwinings of Markov semigroups, for proving theorems about hitting-time distributions for finite-state Markov chains -- an approach that (sometimes) deepens understanding of the…

Probability · Mathematics 2012-09-04 James Allen Fill , Vince Lyzinski

Mahlmann and Schindelhauer (2005) defined a Markov chain which they called $k$-Flipper, and showed that it is irreducible on the set of all connected regular graphs of a given degree (at least 3). We study the 1-Flipper chain, which we call…

Discrete Mathematics · Computer Science 2018-06-14 Colin Cooper , Martin Dyer , Catherine Greenhill , Andrew Handley

We construct different classes of lumpings for a family of Markov chain products which reflect the structure of a given finite poset. We use essentially combinatorial methods. We prove that, for such a product, every lumping can be obtained…

Combinatorics · Mathematics 2013-10-15 Daniele D'Angeli , Alfredo Donno

Given a finite Markov chain, we investigate the first minors of the transition matrix of a lifting of this Markov chain to covering trees. In a simple case we exhibit a nice factorisation of these minors, and we conjecture that it holds…

Combinatorics · Mathematics 2014-12-31 Philippe Biane

Stochastic Kronecker graphs are a model for complex networks where each edge is present independently according the Kronecker (tensor) product of a fixed matrix k-by-k matrix P with entries in [0,1]. We develop a novel correspondence…

Combinatorics · Mathematics 2015-04-02 Mary Radcliffe , Stephen J. Young

We extend Andersson-Madigan-Perlman chain graphs by (i) relaxing the semidirected acyclity constraint so that only directed cycles are forbidden, and (ii) allowing up to two edges between any pair of nodes. We introduce global, and ordered…

Machine Learning · Statistics 2016-02-22 Jose M. Peña

We consider general Markov chains with discrete time in an arbitrary measurable (phase) space and homogeneous in time. Markov chains are defined by the classical transition function which within the framework of the operator treatment…

Probability · Mathematics 2020-06-17 Alexander I. Zhdanok

Starting from any graph on $\{1, \ldots, n\}$, consider the Markov chain where at each time-step a uniformly chosen vertex is disconnected from all of its neighbors and reconnected to another uniformly chosen vertex. This Markov chain has a…

Probability · Mathematics 2021-09-09 François Bienvenu , Jean-Jil Duchamps , Félix Foutel-Rodier

Let $d >1$ and $(A_n)_{n \ge 1}$ be a sequence of independent identically distributed random matrices with nonnegative entries and no zero column. This induces a Markov chain $M_n = A_n M_{n-1}$ on the cone of d-vectors with nonnegative…

Probability · Mathematics 2014-03-17 Sebastian Mentemeier

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

In this paper, we propose to study a general notion of a down-up Markov chain for multifurcating trees with n labelled leaves. We study in detail down-up chains associated with the $(\alpha, \gamma)$-model of Chen et al. (2009),…

Probability · Mathematics 2020-09-23 Frederik Sørensen

We investigate the mixing properties of a model of reversible Markov chains in random environment, which notably contains the simple random walk on the superposition of a deterministic graph and a second graph whose vertex set has been…

Probability · Mathematics 2026-05-13 Bastien Dubail

Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ease with which they can be probed analytically.…

Machine Learning · Computer Science 2023-12-18 Eddie Seabrook , Laurenz Wiskott
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