A Perfect Sampling Algorithm of Random Walks with Forbidden Arcs

Stéphane Durand, Bruno Gaujal, Florence Perronnin, Jean-Marc Vincent

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.