Geodesic
Directed forests with application to algorithms related to Markov chains
Applicationes Mathematicae, Tome 26 (1999) no. 4, pp. 395-414.

Voir la notice de l'article provenant de la source Institute of Mathematics Polish Academy of Sciences

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.
DOI : 10.4064/am-26-4-395-414
Keywords: entrywise relative error, directed forest, Matrix Tree Theorem, directed graph, Simulated Annealing, Markov chains, Metropolis algorithm, direct methods for linear systems, nearly completely decomposable Markov chains, aggregation algorithms, nonhomogeneous Markov chains, Markov Chain Tree Theorem, Markov chain Monte Carlo algorithms, Gibbs sampler

Piotr Pokarowski 1

1 
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Piotr Pokarowski. Directed forests with application to algorithms related to Markov chains. Applicationes Mathematicae, Tome 26 (1999) no. 4, pp. 395-414. doi : 10.4064/am-26-4-395-414. http://geodesic.mathdoc.fr/articles/10.4064/am-26-4-395-414/

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