
Accession Number : ADA119232
Title : Regenerative Aspects of the SteadyState Simulation Problem for Markov Chains.
Descriptive Note : Technical rept.,
Corporate Author : STANFORD UNIV CA DEPT OF OPERATIONS RESEARCH
Personal Author(s) : Glynn,Peter W
PDF Url : ADA119232
Report Date : Jul 1982
Pagination or Media Count : 47
Abstract : The general discreteevent simulation can be viewed, by using the technique of supplementary variables, as a Markov chain living in a general state space. For such chains, we can define in precise terms, the notion of an associated wellposed steadystate simulation problem. We prove that the concept of wellposedness is equivalent to assuming that the Markov chain has regeneratetype structure. These two conditions are, in turn, equivalent to assuming a certain smoothness on the transition probabilities of the chain. We also consider two examples which illustrate how a chain can fail to have regeneratetype structure. (Author)
Descriptors : *Markov processes, *Mathematical models, *Steady state, Simulation, Stochastic processes, Estimates, Confidence limits, Translations, Probability
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE