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Notes: Conditions for the Applicability of the Regenerative Method

Author

Listed:
  • Peter W. Glynn

    (Department of Operations Research, Stanford University, Stanford, California 94305)

  • Donald L. Iglehart

    (Department of Operations Research, Stanford University, Stanford, California 94305)

Abstract

The regenerative method for estimating steady-state parameters is one of the basic methods in simulation output analysis. This method depends on central limit theorems for regenerative processes and weakly consistent estimates for the variance constants arising in the central limit theorems. A weak sufficient condition for both the central limit theorems and consistent estimates is given. Previous authors have implicitly made stronger moment assumptions which have led to strongly consistent variance estimates, more than is needed for the regenerative method to hold. The relationship between conditions for the validity of the regenerative method and those for the validity of standardized time series methods is also discussed.

Suggested Citation

  • Peter W. Glynn & Donald L. Iglehart, 1993. "Notes: Conditions for the Applicability of the Regenerative Method," Management Science, INFORMS, vol. 39(9), pages 1108-1111, September.
    • Handle: RePEc:inm:ormnsc:v:39:y:1993:i:9:p:1108-1111
    DOI: 10.1287/mnsc.39.9.1108
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    Cited by:

    1. Barry L. Nelson, 2004. "50th Anniversary Article: Stochastic Simulation Research in Management Science," Management Science, INFORMS, vol. 50(7), pages 855-868, July.
    2. T. P. I. Ahamed & V. S. Borkar & S. Juneja, 2006. "Adaptive Importance Sampling Technique for Markov Chains Using Stochastic Approximation," Operations Research, INFORMS, vol. 54(3), pages 489-504, June.
    3. Shane G. Henderson & Peter W. Glynn, 1999. "Derandomizing Variance Estimators," Operations Research, INFORMS, vol. 47(6), pages 907-916, December.

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