Lifting -- A nonreversible Markov chain Monte Carlo Algorithm [PDF]
arXiv, 2014 Markov chain Monte Carlo algorithms are invaluable tools for exploring stationary properties of physical systems, especially in situations where direct sampling is unfeasible. Common implementations of Monte Carlo algorithms employ reversible Markov chains. Reversible chains obey detailed balance and thus ensure that the system will eventually relax to
arxiv
On the Vere-Jones classification and existence of maximal measures for countable topological Markov chains [PDF]
Pacific J. Math., 209, No. 2, 365-380, 2003, 2019 We consider topological Markov chains (also called Markov shifts) on countable graphs. We show that a transient graph can be extended to a recurrent graph of equal entropy which is either positive recurrent of null recurrent, and we give an example of each type.
arxiv
Anomalous Recurrence Properties of Markov Chains on Manifolds of Negative Curvature [PDF]
arXiv, 2020 We present a recurrence-transience classification for discrete-time Markov chains on manifolds with negative curvature. Our classification depends only on geometric quantities associated to the increments of the chain, defined via the Riemannian exponential map.
arxiv
A Full-State Reliability Analysis Method for Remanufactured Machine Tools Based on Meta Action and a Markov Chain Using an Exercise Machine (EM) as an Example [PDF]
, 2023 Yueping Luo, Yongmao Xiao
openalex +1 more source
On Mixing Properties of Reversible Markov Chains [PDF]
arXiv, 2014 It is well known that for a strictly stationary, reversible, Harris recurrent Markov chain, the $\rho$-mixing condition is equivalent to geometric ergodicity and to a "spectral gap" condition. In this note, it will be shown with an example that for that class of Markov chains, the "interlaced" variant of the $\rho$-mixing condition fails to be ...
arxiv
Computable Convergence Rates for Subgeometrically Ergodic Markov Chains [PDF]
arXiv, 2005 In this paper, we give quantitative bounds on the $f$-total variation distance from convergence of an Harris recurrent Markov chain on an arbitrary under drift and minorisation conditions implying ergodicity at a sub-geometric rate. These bounds are then specialized to the stochastically monotone case, covering the case where there is no minimal ...
arxiv
Induction of Markov chains, drift functions and application to the LLN, the CLT and the LIL with a random walk on $\mathbb{R}_+$ as an example [PDF]
, 2015 Jean-Baptiste Boyer
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Sweave Documentation for "Implementing Markov chain Monte Carlo: Estimating with confidence" [PDF]
arXiv, 2010 This file is the Sweave documentation for the examples provided in Flegal, J. M. and Jones, G. L. (2010), "Implementing Markov chain Monte Carlo: Estimating with confidence", in Handbook of Markov Chain Monte Carlo, edited by Brooks, S., Gelman, A., Jones, G., and Meng, X. published by Chapman & Hall/CRC Press.
arxiv
Dependent Discrete Risk Processes - Calculation of the Probability of Ruin
Operations Research and Decisions, 2010 This paper is devoted to discrete processes of dependent risks. The random variables describing the time between claims can be dependent in such processes, unlike under the classical approach.
Stanisław Heilpern
doaj
Analyticity of Entropy Rate of Hidden Markov Chains [PDF]
arXiv, 2005 We prove that under mild positivity assumptions the entropy rate of a hidden Markov chain varies analytically as a function of the underlying Markov chain parameters. A general principle to determine the domain of analyticity is stated. An example is given to estimate the radius of convergence for the entropy rate.
arxiv