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A perfect sampling algorithm of random walks with forbidden arcs

Stéphane Durand 1 Bruno Gaujal 1, * Florence Perronnin 1 Jean-Marc Vincent 1 
* Corresponding author
1 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : In this paper we show how to construct an algorithm to sample the stationary distribution of a random walk over a grid 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 that is logarithmic in the size of the grid, when no arc is forbidden, and an experimental study of its performance.
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Submitted on : Monday, March 24, 2014 - 9:47:50 AM
Last modification on : Wednesday, October 26, 2022 - 8:16:01 AM
Long-term archiving on: : Tuesday, June 24, 2014 - 11:01:19 AM


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  • HAL Id : hal-00964098, version 1


Stéphane Durand, Bruno Gaujal, Florence Perronnin, Jean-Marc Vincent. A perfect sampling algorithm of random walks with forbidden arcs. [Research Report] RR-8504, INRIA. 2014, pp.23. ⟨hal-00964098⟩



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