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Simulating Stable Stochastic Systems, IV: Approximation Techniques

Author

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  • Michael A. Crane

    (Control Analysis Corporation)

  • Donald L. Iglehart

    (Stanford University)

Abstract

The previous papers in this series developed a methodology for obtaining from certain simulations confidence intervals for parameters associated with the steady-state distribution. This methodology required the simulations to contain an embedded renewal process at whose epochs the simulation started from scratch. The present paper contains four approximation techniques for obtaining confidence intervals when the simulation does not contain the required renewal process.

Suggested Citation

  • Michael A. Crane & Donald L. Iglehart, 1975. "Simulating Stable Stochastic Systems, IV: Approximation Techniques," Management Science, INFORMS, vol. 21(11), pages 1215-1224, July.
    • Handle: RePEc:inm:ormnsc:v:21:y:1975:i:11:p:1215-1224
    DOI: 10.1287/mnsc.21.11.1215
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    Cited by:

    1. Christos Alexopoulos & David Goldsman & Anup C. Mokashi & Kai-Wen Tien & James R. Wilson, 2019. "Sequest: A Sequential Procedure for Estimating Quantiles in Steady-State Simulations," Operations Research, INFORMS, vol. 67(4), pages 1162-1183, July.
    2. Koike, Takaaki & Saporito, Yuri & Targino, Rodrigo, 2022. "Avoiding zero probability events when computing Value at Risk contributions," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 173-192.
    3. George, Halkos & Ilias, Kevork, 2004. "H Ασυμπτωτική Διακύμανση Στην Εκτίμηση Του Στάσιμου Μέσου Υπό Συνθήκες Αυτοσυσχέτισης [Using the asymptotic variance to estimate the stationary mean under autocorrelation]," MPRA Paper 33324, University Library of Munich, Germany.
    4. Halkos, George & Kevork, Ilias, 2002. "Confidence intervals in stationary autocorrelated time series," MPRA Paper 31840, University Library of Munich, Germany.
    5. Leroudier, Jacques & Parent, Michel, 1979. "Discrete event simulation modelling of computer systems for performance evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 21(1), pages 50-79.
    6. Halkos, George & Kevork, Ilias, 2006. "Estimating population means in covariance stationary process," MPRA Paper 31843, University Library of Munich, Germany.

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