Perfect simulation for Markov chains arising from discrete-event simulation. Henderson, S. & Tweedie, R. In Sreenivas, R. & Jones, D., editors, *Proceedings of the 38th Annual Allerton Conference on Communication, Control, and Computing*, pages 1125–1134, Urbana-Champaign, Illinois, 2000. University of Illinois.

Paper abstract bibtex

Paper abstract bibtex

Virtually any discrete-event simulation can be rigorously defined as a Markov chain evolving on a general state space, and under appropriate conditions, the chain has a unique stationary probability distribution. Many steady-state performance measures can be expressed in terms of the stationary probability distribution of the chain. We would like to apply ``coupling from the past'' algorithms to obtain samples from the stationary probability distribution of such chains. Unfortunately, the structural properties of the chains arising from discrete-event simulations preclude the immediate application of current coupling from the past algorithms. We describe why this is the case, and extend a class of coupling from the past algorithms so that they may be applied in this setting.

@inproceedings{hentwe00, abstract = {Virtually any discrete-event simulation can be rigorously defined as a Markov chain evolving on a general state space, and under appropriate conditions, the chain has a unique stationary probability distribution. Many steady-state performance measures can be expressed in terms of the stationary probability distribution of the chain. We would like to apply ``coupling from the past'' algorithms to obtain samples from the stationary probability distribution of such chains. Unfortunately, the structural properties of the chains arising from discrete-event simulations preclude the immediate application of current coupling from the past algorithms. We describe why this is the case, and extend a class of coupling from the past algorithms so that they may be applied in this setting.}, address = {Urbana-Champaign, Illinois}, author = {S.~G.\ Henderson and R.~L.\ Tweedie}, booktitle = {Proceedings of the 38th Annual Allerton Conference on Communication, Control, and Computing}, date-added = {2016-01-10 16:07:54 +0000}, date-modified = {2016-01-10 16:07:54 +0000}, editor = {R.~S.\ Sreenivas and D.~L.\ Jones}, organization = {University of Illinois}, pages = {1125--1134}, title = {Perfect simulation for {M}arkov chains arising from discrete-event simulation}, url_paper = {pubs/HendersonTweedie.pdf}, year = 2000}

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Unfortunately, the structural properties of the chains arising from discrete-event simulations preclude the immediate application of current coupling from the past algorithms. 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Many steady-state performance measures can be expressed in terms of the stationary probability distribution of the chain.\n\t\nWe would like to apply ``coupling from the past'' algorithms to obtain samples from the stationary probability distribution of such chains. Unfortunately, the structural properties of the chains arising from discrete-event simulations preclude the immediate application of current coupling from the past algorithms. 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