Variance reduction for simulation practitioners

ABSTRACT

A comprehensive guide to applying three well-known variance reduction techniques is given, including point and interval estimators, software requirements, and guidelines for experiment design.

REFERENCES

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• 2: Paul Bratley , Bennett L Fox , Linus E Schrage, A guide to simulation (2nd ed.), Springer-Verlag New York, Inc., New York, NY, 1986
• 3: Gordon M. Clark , Wei-ning Yang, A Bonferroni selection procedure when using commom random numbers with unknown variances, Proceedings of the 18th conference on Winter simulation, p.313-315, December 08-10, 1986, Washington, D.C., United States [doi>10.1145/318242.318452]
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• 17: Schmeiser, B. (1982). Batch Size Effects in "the Analysis of Simulation Output. Operations Research 30, 556-568.
• 18: Schruben, L.W. and B.H. Margolin (1978). Pseudorandom Number Assignment in Statistically Designed Simulation and Distribution Sampling Experiments. Journal of the American Statistical Association 73, 504-525.
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• 20: Venkatraman, S. and J.R. Wilson (1986). The Efficiency of Control Variates in Multiresponse Simulation. Operations Research Letters 5, 37-42.
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INDEX TERMS

Primary Classification:
  A. General Literature

Additional Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING

General Terms:
Design, Experimentation, Measurement, Performance, Theory