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Asymptotic Validity of Batch Means Steady-State Confidence Intervals

In: Advancing the Frontiers of Simulation

Author

Listed:
  • Peter W. Glynn

    (Stanford University)

  • Eunji Lim

    (University of Miami)

Abstract

The method of batch means is a widely applied procedure for constructing steady-state confidence intervals. The traditional theoretical support for the method of batch means has rested on the assumption of a functional central limit theorem for the underlying process. We establish here that the method of batch means is valid for Harris recurrent Markov processes whenever the associated process satisfies a simple (non–functional) central limit theorem. This weaker condition for validity of the method of batch means is also shown to hold in the setting of one-dependent regenerative processes.

Suggested Citation

  • Peter W. Glynn & Eunji Lim, 2009. "Asymptotic Validity of Batch Means Steady-State Confidence Intervals," International Series in Operations Research & Management Science, in: Christos Alexopoulos & David Goldsman & James R. Wilson (ed.), Advancing the Frontiers of Simulation, pages 87-104, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-0817-9_5
    DOI: 10.1007/b110059_5
    as

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