Accession Number : ADA119232

Title :   Regenerative Aspects of the Steady-State 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 discrete-event 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 well-posed steady-state simulation problem. We prove that the concept of well-posedness is equivalent to assuming that the Markov chain has regenerate-type 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 regenerate-type 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