Variance reduction for quantile estimation via correlation induction

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Variance reduction for quantile estimation via correlation induction

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Winter Simulation Conference archive
Proceedings of the 24th conference on Winter simulation table of contents

Arlington, Virginia, United States

Pages: 572 - 576

Year of Publication: 1992

ISBN:0-7803-0798-4

Author

Athanassios N. Avramidis

Sponsors

ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
ORSA : Operations Research Society of America
SIGSIM: ACM Special Interest Group on Simulation and Modeling
TIMS :
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation

Publisher

ACM New York, NY, USA

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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	2	Avramidis, A. N., K. W. Bauer, and J. R. Wilson. 1991. Simulation of s~ochastic activity networks using path control variates. Naval Research Logistics 38:183-201.
	3	David, H. A. Order Statislzcs. 1981. 2d ed. New York: Wiley.
	4	J. C. Hsu , B. L. Nelson, Control variates for quantile estimation, Management Science, v.36 n.7, p.835-851, Jul. 1990 [doi>10.1287/mnsc.36.7.835]
	5	Juritz, J. M., J. W. F. Juritz, and M. A. Stephens. 1983. On the accuracy of simulated percentage points. Journal of the American Statislical Association 78:441-444.
	6	Lehmann, E. L. 1966. Some Concepts of Dependence. Annals of Mathematical Stalistics 37:1137-1153.
	7	P. A. W. Lewis , R. L. Ressler, Variance reduction of quantile estimates via nonlinear control, Proceedings of the 21st conference on Winter simulation, p.450-454, December 04-06, 1989, Washington, D.C., United States [doi>10.1145/76738.76795]
	8	McKay, M. D., R. J. Beckman, and W. J. Conover. 1979. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technomelrics 21:239-245.
	9	Schafer, P~. E. 1974. On assessing the Precision of Simulation. Journal of Statistical Compuialion and Simulaiion 3:67-69.
	10	Michael Stein, Large sample properties of simulations using latin hypercube sampling, Technometrics, v.29 n.2, p.143-151, May 1, 1987 [doi>10.2307/1269769]
	11	van Zwet, W. R. 1964. Convex Transformations of Random Variables. Mathematical Center Tracts 7, Mathematisch Centrum, Amsterdam.
	12	Zelterman, D. 1987. Estimating Percentage Points by Simulation. Journal of Statistical Compuialion and Simulation 27:107-125.