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.
This work was partially supported by ANR Marmote project ANR-12-MONU-0019.
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Durand, S., Gaujal, B., Perronnin, F., Vincent, JM. (2014). A Perfect Sampling Algorithm of Random Walks with Forbidden Arcs. In: Norman, G., Sanders, W. (eds) Quantitative Evaluation of Systems. QEST 2014. Lecture Notes in Computer Science, vol 8657. Springer, Cham. https://doi.org/10.1007/978-3-319-10696-0_15
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DOI: https://doi.org/10.1007/978-3-319-10696-0_15
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