How to combine fast heuristic Markov chain Monte Carlo with slow exact sampling.
Bandyopadhyay, Antar, Aldous, David J. (2001)
Electronic Communications in Probability [electronic only]
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Displaying similar documents to “Cutoff for samples of Markov chains”
How to combine fast heuristic Markov chain Monte Carlo with slow exact sampling.
Reduction of absorbing Markov chain
Mariusz Górajski (2009)
Annales UMCS, Mathematica
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In this paper we consider an absorbing Markov chain with finite number of states. We focus especially on random walk on transient states. We present a graph reduction method and prove its validity. Using this method we build algorithms which allow us to determine the distribution of time to absorption, in particular we compute its moments and the probability of absorption. The main idea used in the proofs consists in observing a nondecreasing sequence of stopping times. Random walk on...
The tail structure of nonhomogeneous finite state Markov chains: survey
Marius Losifescu (1979)
Banach Center Publications
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Edge occupation measure for a reversible Markov chain.
Guillotin, N. (1999)
Electronic Communications in Probability [electronic only]
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Regeneration and general Markov chains.
Kalashnikov, Vladimir V. (1994)
Journal of Applied Mathematics and Stochastic Analysis
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On the fundamental matrix of finite state Markov chains, its eigensystem and its relation to hitting times.
Takacs, Christiane (2006)
Mathematica Pannonica
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Technical comment. A problem on Markov chains
Franco Giannessi (2002)
RAIRO - Operations Research - Recherche Opérationnelle
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A problem (arisen from applications to networks) is posed about the principal minors of the matrix of transition probabilities of a Markov chain.
Directed forests with application to algorithms related to Markov chains
Piotr Pokarowski (1999)
Applicationes Mathematicae
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This paper is devoted to computational problems related to Markov chains (MC) on a finite state space. We present formulas and bounds for characteristics of MCs using directed forest expansions given by the Matrix Tree Theorem. These results are applied to analysis of direct methods for solving systems of linear equations, aggregation algorithms for nearly completely decomposable MCs and the Markov chain Monte Carlo procedures.
Simple Markov chains
O. Adelman (1976)
Annales scientifiques de l'Université de Clermont. Mathématiques
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Geometric ergodicity for a class of Markov chains
E. Nummelin, R. L. Tweedie (1976)
Annales scientifiques de l'Université de Clermont. Mathématiques
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