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Markov combination is an operation that takes two statistical models and produces a third whose marginal distributions include those of the original models. Building upon and extending existing work in the Gaussian case, we develop Markov…

Statistics Theory · Mathematics 2025-09-24 Orlando Marigliano , Eva Riccomagno

This text is written based on the author's publications during the period from 1991 to 2001. The work is devoted to the theory of Markov intertwining operators and joinings of measure-preserving group actions, as well as to their…

Dynamical Systems · Mathematics 2021-03-15 Valery V. Ryzhikov

In the present paper, we consider random invariant densities and the mean ergodic theorem for Markov operator cocycles which are applicable to quenched type random dynamical systems. We give necessary and sufficient conditions for the…

Dynamical Systems · Mathematics 2022-07-27 Fumihiko Nakamura , Hisayoshi Toyokawa

In this paper we establish a large deviations type estimate for strongly mixing Markov chains with respect to the Lp norm. As applications we derive such estimates for the iterates of a locally constant random cocycle with mixed rank, as…

Dynamical Systems · Mathematics 2026-02-10 Anselmo Pontes

We develop operator renewal theory for flows and apply this to infinite ergodic theory. In particular we obtain results on mixing for a large class of infinite measure semiflows. Examples of systems covered by our results include…

Dynamical Systems · Mathematics 2014-04-11 Ian Melbourne , Dalia Terhesiu

The paper deals with the problem of long-time asymptotic behaviour of solutions for classes of ODEs and PDEs, perturbed by stationary noises. The latter are not assumed to be $\delta$-correlated in time, so that the evolution in question is…

Probability · Mathematics 2025-12-29 Sergei Kuksin , Armen Shirikyan

In this work, we characterise the statistics of Markov chains by constructing an associated sequence of periodic differential operators. Studying the density of states of these operators reveals the absolutely continuous invariant measure…

Dynamical Systems · Mathematics 2025-09-22 Bryn Davies , Angelica Yu Xiao

We establish an abstract, effective, exponential large deviations type estimate for Markov systems satisfying a weaker form of mixing. We employ this result to derive such estimates, as well as a central limit theorem, for the skew product…

Dynamical Systems · Mathematics 2025-07-17 Ao Cai , Pedro Duarte , Silvius Klein

We address the problem of community detection in networks by introducing a general definition of Markov stability, based on the difference between the probability fluxes of a Markov chain on the network at different time scales. The…

Physics and Society · Physics 2020-05-05 Aurelio Patelli , Andrea Gabrielli , Giulio Cimini

We consider Markovian models on graphs with local dynamics. We show that, under suitable conditions, such Markov chains exhibit both rapid convergence to equilibrium and strong concentration of measure in the stationary distribution. We…

Probability · Mathematics 2008-09-30 Malwina J. Luczak

We formalize and analyze the notions of stochastic monotonicity and realizable mono-tonicity for Markov Chains in continuous-time, taking values in a finite partially ordered set. Similarly to what happens in discrete-time, the two notions…

Probability · Mathematics 2016-03-08 Paolo Dai Pra , Pierre-Yves Louis , Ida Minelli

When two Markov operators commute, it suggests that we can couple two copies of one of the corresponding processes. We explicitly construct a number of couplings of this type for a commuting family of Markov processes on the set of…

Probability · Mathematics 2008-11-20 Anthony P. Metcalfe , Neil O'Connell , Jon Warren

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

We study the stochastic dynamics of a system of interacting species in a stochastic environment by means of a continuous-time Markov chain with transition rates depending on the state of the environment. Models of gene regulation in systems…

Dynamical Systems · Mathematics 2019-12-03 Daniele Cappelletti , Abhishek Pal Majumder , Carsten Wiuf

We prove measurable Livsic theorems for dynamical systems modelled by Markov Towers. Our regularity results apply to solutions of cohomological equations posed on Henon-like mappings and a wide variety of nonuniformly hyperbolic systems. We…

Dynamical Systems · Mathematics 2007-05-23 Henk Bruin , Mark Holland , Matthew Nicol

This paper addresses the problem of verifying discrete-time stochastic systems against omega-regular specifications using finite-state abstractions. Omega-regular properties allow specifying complex behavior and encompass, for example,…

Signal Processing · Electrical Eng. & Systems 2020-01-31 Maxence Dutreix , Samuel Coogan

A definition of metastable states applicable to arbitrary finite state Markov processes satisfying detailed balance is discussed. In particular, we identify a crucial condition that distinguishes genuine metastable states from other types…

Statistical Mechanics · Physics 2016-08-31 Francois Leyvraz , Hernan Larralde , David P. Sanders

A class of examples is constructed to show that for strictly stationary Markov chains that are reversible, the simultaneous mixing rates for the $\rho$-mixing and strong mixing ($\alpha$-mixing) conditions can be fairly arbitrary, within…

Probability · Mathematics 2022-10-04 Richard C. Bradley

The exponential rate of convergence and the Central Limit Theorem for some Markov operators are established. The operators correspond to iterated function systems which, for example, may be used to generalize the cell cycle model given by…

Probability · Mathematics 2017-01-03 Sander Hille , Katarzyna Horbacz , Tomasz Szarek , Hanna Wojewódka

We analyze the notions of monotonicity and complete monotonicity for Markov Chains in continuous-time, taking values in a finite partially ordered set. Similarly to what happens in discrete-time, the two notions are not equivalent. However,…

Probability · Mathematics 2016-03-08 Paolo Dai Pra , Pierre-Yves Louis , Ida Minelli
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