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 dlogd) when no arc is forbidden and an experimental study of its performance. © 2014 Springer International Publishing.
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Durand, S., Gaujal, B., Perronnin, F., & Vincent, J. M. (2014). A perfect sampling algorithm of random walks with forbidden arcs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8657 LNCS, pp. 178–193). Springer Verlag. https://doi.org/10.1007/978-3-319-10696-0_15
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