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Variance reduction: The current state

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  • Wilson, James R.

Abstract

Estimation efficiency is an increasingly important issue in the design and analysis of large-scale simulation experiments. This paper surveys recent research on the major variance reduction techniques that have been developed for or adapted to Monte Carlo studies. Current unresolved problems and directions for future research are also discussed.

Suggested Citation

  • Wilson, James R., 1983. "Variance reduction: The current state," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 25(1), pages 55-59.
    • Handle: RePEc:eee:matcom:v:25:y:1983:i:1:p:55-59
    DOI: 10.1016/0378-4754(83)90032-0
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    References listed on IDEAS

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    1. Hopmans, A.C.M. & Kleijnen, J.P.C., 1979. "Importance sampling in systems simulation: a practical failure?," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 21(2), pages 209-220.
    2. S. S. Lavenberg & T. L. Moeller & C. H. Sauer, 1979. "Concomitant Control Variables Applied to the Regenerative Simulation of Queuing Systems," Operations Research, INFORMS, vol. 27(1), pages 134-160, February.
    3. Stephen S. Lavenberg & Thomas L. Moeller & Peter D. Welch, 1982. "Statistical Results on Control Variables with Application to Queueing Network Simulation," Operations Research, INFORMS, vol. 30(1), pages 182-202, February.
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