Perfect sampling of stationary rewards of Markov chains

Jean-Marc Vincent 1
1 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : This article illustrates how reward backward coupling improves simulation complexity for the estimation of stationary rewards. Bounds on the coupling time for M/M/1/C are given and experimental results on a large queueing network validate the practical interest of such an approach.
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Jean-Marc Vincent. Perfect sampling of stationary rewards of Markov chains. International Workshop on Applied Probability, 2008, Compiègne, France. ⟨hal-00953625⟩

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