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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

Random walks cannot, in general, be pushed forward by quasi-isometries. Tame Markov chains were introduced as a `quasi-isometry invariant' are a generalization of random walks. In this paper, we construct several examples of tame Markov…

Group Theory · Mathematics 2023-09-27 Antoine Goldsborough , Stefanie Zbinden

A Markov process fluctuating away from its typical behavior can be represented in the long-time limit by another Markov process, called the effective or driven process, having the same stationary states as the original process conditioned…

Statistical Mechanics · Physics 2023-03-30 Florian Angeletti , Hugo Touchette

We consider a class of small-sample distribution estimators over noisy channels. Our estimators are designed for repetition channels, and rely on properties of the runs of the observed sequences. These runs are modeled via a special type of…

Information Theory · Computer Science 2012-02-07 Farzad Farnoud , Narayana P. Santhanam , Olgica Milenkovic

The main goal of this text is comprehensive study of time homogeneous Markov chains on the real line whose drift tends to zero at infinity, we call such processes Markov chains with asymptotically zero drift. Traditionally this topic is…

Probability · Mathematics 2023-09-06 Denis Denisov , Dmitry Korshunov , Vitali Wachtel

In this paper, we establish moment and Bernstein-type inequalities for additive functionals of geometrically ergodic Markov chains. These inequalities extend the corresponding inequalities for independent random variables. Our conditions…

Probability · Mathematics 2023-06-16 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov

This paper gives a method for computing distributions associated with patterns in the state sequence of a hidden Markov model, conditional on observing all or part of the observation sequence. Probabilities are computed for very general…

Methodology · Statistics 2007-12-18 John A. D. Aston , Donald E. K. Martin

Monte Carlo (MC) simulations of transport in random porous networks indicate that for high variances of the log-normal permeability distribution, the transport of a passive tracer is non-Fickian. Here we model this non-Fickian dispersion in…

Computational Physics · Physics 2018-08-01 Amir H. Delgoshaie , Patrick Jenny , Hamdi A. Tchelepi

Our investigation is specially motivated by the stochastic version of a common model of potential spread in a dendritic tree. We do not assume the noise in the junction points to be Markovian. In fact, we allow for long-range dependence in…

Probability · Mathematics 2018-12-21 Stefano Bonaccorsi , Delio Mugnolo

In this work we present a modified neural network model which is capable to simulate Markov Chains. We show how to express and train such a network, how to ensure given statistical properties reflected in the training data and we…

Machine Learning · Computer Science 2018-05-03 Maren Awiszus , Bodo Rosenhahn

This article considers a model for alternative processes for securities prices and compares this model with actual return data of several securities. The distributions of returns that appear in the model can be Gaussian as well as…

Adaptation and Self-Organizing Systems · Physics 2008-12-02 Kyrylo Shmatov , Mikhail Smirnov

It is shown that the combinatorics of commutation relations is well suited for analyzing the convergence rate of certain Markov chains. Examples studied include random walk on irreducible representations, a local random walk on partitions…

Probability · Mathematics 2008-01-21 Jason Fulman

When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform a sensitivity analysis. This can be done by considering as basic uncertainty models the so-called credal sets that…

Probability · Mathematics 2009-11-24 Gert de Cooman , Filip Hermans , Erik Quaeghebeur

In the present Short Note an idea is proposed to explain the emergence and the observation of processes in complex media that are driven by fractional non-Markovian master equations. Particle trajectories are assumed to be solely Markovian…

Statistical Mechanics · Physics 2015-06-19 Gianni Pagnini

A general theory is developed to study individual based models which are discrete in time. We begin by constructing a Markov chain model that converges to a one-dimensional map in the infinite population limit. Stochastic fluctuations are…

Statistical Mechanics · Physics 2014-06-03 Joseph D. Challenger , Duccio Fanelli , Alan J. McKane

We consider Markov-switching regression models, i.e. models for time series regression analyses where the functional relationship between covariates and response is subject to regime switching controlled by an unobservable Markov chain.…

Methodology · Statistics 2015-05-12 Roland Langrock , Thomas Kneib , Richard Glennie , Théo Michelot

We consider random walks on dynamical networks where edges appear and disappear during finite time intervals. The process is grounded on three independent stochastic processes determining the walker's waiting-time, the up-time and down-time…

Physics and Society · Physics 2018-11-28 Julien Petit , Martin Gueuning , Timoteo Carletti , Ben Lauwens , Renaud Lambiotte

The investigation of the phenomenon of dephasing assisted quantum transport, which happens when the presence of dephasing benefits the efficiency of this process, has been mainly focused on Markovian scenarios associated with constant and…

Quantum Physics · Physics 2022-01-27 Saulo V. Moreira , Breno Marques , Fernando L. Semião

In this letter we announce rigorous results that elucidate the relation between metastable states and low-lying eigenvalues in Markov chains in a much more general setting and with considerable greater precision as was so far available.…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Bovier , M. Eckhoff , V. Gayrard , M. Klein

We study the large deviations of Markov chains under the sole assumption that the state space is discrete. In particular, we do not require any of the usual irreducibility and exponential tightness assumptions. Using subadditive arguments,…

Probability · Mathematics 2026-05-15 Léo Daures
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