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Confidence Intervals for Steady-State Simulations II: A Survey of Sequential Procedures

Author

Listed:
  • Averill M. Law

    (University of Arizona)

  • W. David Kelton

    (Kent State University)

Abstract

We continue our survey of methods for constructing confidence intervals for steady-state means via simulation by studying sequential procedures which determine the length of the simulation during the course of the run. Our goal is to provide the simulation practitioner with some guidance as to which published procedures might actually perform well in practice. Empirical results for a variety of stochastic models with known steady-state means suggest that sequential procedures by Fishman and by Law and Carson provide good performance relative to the criterion probability of coverage.

Suggested Citation

  • Averill M. Law & W. David Kelton, 1982. "Confidence Intervals for Steady-State Simulations II: A Survey of Sequential Procedures," Management Science, INFORMS, vol. 28(5), pages 550-562, May.
    • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:5:p:550-562
    DOI: 10.1287/mnsc.28.5.550
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    Cited by:

    1. K Hoad & S Robinson & R Davies, 2010. "Automated selection of the number of replications for a discrete-event simulation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(11), pages 1632-1644, November.
    2. Barry L. Nelson, 2004. "50th Anniversary Article: Stochastic Simulation Research in Management Science," Management Science, INFORMS, vol. 50(7), pages 855-868, July.
    3. Ayvaz, Berk & Bolat, Bersam & Aydın, Nezir, 2015. "Stochastic reverse logistics network design for waste of electrical and electronic equipment," Resources, Conservation & Recycling, Elsevier, vol. 104(PB), pages 391-404.
    4. Halkos, George & Kevork, Ilias, 2002. "Confidence intervals in stationary autocorrelated time series," MPRA Paper 31840, University Library of Munich, Germany.
    5. Halkos, George & Kevork, Ilias, 2006. "Estimating population means in covariance stationary process," MPRA Paper 31843, University Library of Munich, Germany.

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