Accelerated regeneration for markov chain simulations

Sigrún Andradóttir, James M. Calvin, Peter W. Glynnt

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

This paper describes a generalization of the classical regenerative method of simulation output analysis. Instead of blocking a generated sample path on returns to a fixed return state, a more general scheme to randomly decompose the path is used. In some cases, this decomposition scheme results in regeneration times that are a supersequence of the classical regeneration times. This “accelerated” regeneration is advantageous in several simulation contexts. It is shown that when this decomposition scheme accelerates regeneration relative to the classical regenerative method, it also yields a smaller asymptotic variance of the regenerative variance estimator than the classical method. Several other contexts in which increased regeneration frequency is beneficial are also discussed.

Original languageEnglish (US)
Pages (from-to)497-523
Number of pages27
JournalProbability in the Engineering and Informational Sciences
Volume9
Issue number4
DOIs
StatePublished - Oct 1995
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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