# A perfect sampling algorithm of random walks with forbidden arcs

1 MESCAL - Middleware efficiently scalable
LIG - Laboratoire d'Informatique de Grenoble, Inria Grenoble - Rhône-Alpes
Abstract : In this paper we show how to construct an algorithm to sample the stationary distribution of a random walk over ${1,...,N}^d$ with forbidden arcs. This algorithm combines the rejection method and coupling from the past of a set of trajectories of the Markov chain that generalizes the classical sandwich approach. We also provide a complexity analysis of this approach in several cases showing a coupling time in $O(N^2 d log d )$ when no arc is forbidden and an experimental study of its performance.
Document type :
Conference papers

https://hal.inria.fr/hal-01069975
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Submitted on : Tuesday, September 30, 2014 - 11:43:53 AM
Last modification on : Thursday, October 21, 2021 - 3:49:28 AM

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### Citation

Stéphane Durand, Bruno Gaujal, Florence Perronnin, Jean-Marc Vincent. A perfect sampling algorithm of random walks with forbidden arcs. QEST 2014 - 11th International Conference on Quantitative Evaluation of Systems, Sep 2014, Florence, Italy. pp.178-193, ⟨10.1007/978-3-319-10696-0_15⟩. ⟨hal-01069975⟩

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