A Perfect Sampling Algorithm of Random Walks with Forbidden Arcs

被引：0
|
作者：
Durand, Stephane [1 ,4 ]
Gaujal, Bruno [2 ,3 ,4 ]
Perronnin, Florence [2 ,3 ,4 ]
Vincent, Jean-Marc [1 ,2 ,3 ,4 ]
机构：
[1] ENS Lyon, Lyon, France
[2] Univ Grenoble Alpes, LIG, F-38000 Grenoble, France
[3] CNRS, LIG, F-38000 Grenoble, France
[4] Inria, Rocquencourt, France
来源：
QUANTITATIVE EVALUATION OF SYSTEMS, QEST 2014 | 2014年 / 8657卷
关键词：
Perfect simulation; Markov chain; random walks;
D O I：
10.1007/978-3-319-10696-0_15
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：178 / 193
页数：16
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