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Confidence intervals in discrete event simulation: A comparison of replication and batch means

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  • Averill M. Law

Abstract

Suppose that we have enough computer time to make n observations of a stochastic process by means of simulation and would like to construct a confidence interval for the steady‐state mean. We can make k independent runs of m observations each (n=k.m) or, alternatively, one run of n observations which we then divide into k batches of length m. These methods are known as replication and batch means, respectively. In this paper, using the probability of coverage and the half length of a confidence interval as criteria for comparison, we empirically show that batch means is superior to replication, but that neither method works well if n is too small. We also show that if m is chosen too small for replication, then the coverage may decrease dramatically as the total sample size n is increased.

Suggested Citation

  • Averill M. Law, 1977. "Confidence intervals in discrete event simulation: A comparison of replication and batch means," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 24(4), pages 667-678, December.
    • Handle: RePEc:wly:navlog:v:24:y:1977:i:4:p:667-678
    DOI: 10.1002/nav.3800240414
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    Cited by:

    1. Ridler, Samuel & Mason, Andrew J. & Raith, Andrea, 2022. "A simulation and optimisation package for emergency medical services," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1101-1113.

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