Cramér-von Mises variance estimators for simulations

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Cramér-von Mises variance estimators for simulations

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Winter Simulation Conference archive
Proceedings of the 23rd conference on Winter simulation table of contents

Phoenix, Arizona, United States

Pages: 916 - 920

Year of Publication: 1991

ISBN:0-7803-0181-1

Authors

David Goldsman	School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia
Keebom Kang	Department of Administrative Sciences, Naval Postgraduate School, Monterey, California
Andrew F. Seila	Dept. of Management Sciences & Information Technology, University of Georgia, Athens, Georgia

Sponsors

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

Publisher

IEEE Computer Society Washington, DC, USA

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Downloads (6 Weeks): 4, Downloads (12 Months): 11, Citation Count: 1

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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.

	1	Anderson, T. W., and D. A. Darling. 1952. Asymptotic theory of certain 'goodness of fit' criteria ba~ed on stochastic processes. Annals of Maghemagical Statistics 23, 193-212.
	2	Paul Bratley , Bennett L. Fox , Linus E. Schrage, A guide to simulation (2nd ed.), Springer-Verlag New York, Inc., New York, NY, 1987
	3	Cram~r, H. 1928. On the composition of elementary errors. Second paper: statisticM applications. Skand. Aktuartidskr. 11,141-180.
	4	Durbin, J. 1973. Distribution Theory for Tests Based on the Sample Distribnlion Fnnction. Philadelphia: Society for industrial and Applied Mathematics.
	5	Dzhaparidze, K. 1986. Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series, New York: Springer-Verlag.
	6	Foley, R. D., and D. Goldsman. 1990. Confidence intervals using orthonormally weighted standardized time series. Technical Report, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia.
	7	P. W. Glynn , D. L. Iglehart, Simulation output analysis using standardized time series, Mathematics of Operations Research, v.15 n.1, p.1-16, Feb. 1990 [doi>10.1287/moor.15.1.1]
	8	Goldsman, D., K. Kang, and A. F. Seila. 1991. Cram(~r-von Mises variance estimators for simulations. Technical Report, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia.
	9	Goldsman, D., and M. S. Meketon. 1990. A comparison of several variance estimators. Technical Report, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia.
	10	D. Goldsman , M. Meketon , L. Schruben, Properties of standardized time series weighted area variance estimators, Management Science, v.36 n.5, p.602-612, May 1990 [doi>10.1287/mnsc.36.5.602]
	11	Marc S. Meketon , Bruce Schmeiser, Overlapping batch means: something for nothing?, Proceedings of the 16th conference on Winter simulation, p.226-230, December 28-30, 1984, Dallas, TX
	12	Schmeiser, B. W., and W.-M. Song. 1989. Optimal mean-squared-error batch sizes. Technical Report, School of Industrial Engineering, Purdue University, West Lafayette, Indiana.
	13	Schruben, L. 1983. Confidence interval estimation using standardized time series. Operations Research 31, 1090-1108.
	14	Smirnov, N. V. 1937. On the distribution of the von Mises w2-criterion (in Russian). Matem Sbornik. 5, 973-993.
	15	yon Mises, R. 1931. Wahrscheinlichkeitsrechnung. Leipzig" Wein.
	16	Watson, G. S. 1961. Goodness-of-fit tests on a circle. Biometrika 48, 109-114.