A comparison of confidence region estimators for multivariate simulation output

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A comparison of confidence region estimators for multivariate simulation output

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Winter Simulation Conference archive
Proceedings of the 20th conference on Winter simulation table of contents

San Diego, California, United States

Pages: 458 - 465

Year of Publication: 1988

ISBN:0-911801-42-1

Authors

John M. Charnes	Department of Management Sciences, Curtis L. Carlson School of Management, University of Minnesota, Minneapolis, MN
W. David Kelton	Department of Management Sciences, Curtis L. Carlson School of Management, University of Minnesota, Minneapolis, MN

Sponsors

ORS : Orthopaedic Research Society
SIGSIM: ACM Special Interest Group on Simulation and Modeling
TIMS :
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 3, Downloads (12 Months): 19, Citation Count: 9

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ABSTRACT

Three previously proposed methods for constructing joint confidence regions on the mean of multivariate simulation output are described and tested using data generated by Gaussian vector autoregressive moving average models. The methods that use an estimate of the variance-covariance matrix of the data are found to yield regions with lower volumes than the method that does not use an estimate of the variance-covariance matrix. The experimental design included the factors run length, dimension, autocorrelation and cross correlation.

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	Bickel, P.J. and Doksum, K.A. (1977). Mathematical Statistics, Holden-Day.
	2	Der-Fa R. Chen , Andrew F. Seila, Multivariate inference in stationary simulation using batch means, Proceedings of the 19th conference on Winter simulation, p.302-304, December 14-16, 1987, Atlanta, Georgia, United States [doi>10.1145/318371.318436]
	3	George S. Fishman, Principles of Discrete Event Simulation, John Wiley & Sons, Inc., New York, NY, 1978
	4	Fishman, G.S. (1978b). Grouping observations in digital simulation. Management Science 24~, 510-521.
	5	Hannan, E.J. (1970). Multiple Time Series, Wiley: New York.
	6	R. A. Johnson , D. W. Wichern, Applied multivariate statistical analysis, Prentice-Hall, Inc., Upper Saddle River, NJ, 1988
	7	Kabaila P. and G. Nelson (1985). "On confidence regions for the mean of a multivariate time series" Communications in Statistics - Theory and Methods, 14(3), pp. 735-753.
	8	Seila, A.F. (1984). "Multivariate output analysis in discrete event simulation: The state of the art", Working Paper No. 84-151, College of Business Administration, The University of Georgia.

CITED BY 9

	Koichiro Inoue , Stephen E. Chick, Comparison of Bayesian and frequentist assessments of uncertainty for selecting the best system, Proceedings of the 30th conference on Winter simulation, p.727-734, December 13-16, 1998, Washington, D.C., United States
	John M. Charnes, Multivariate simulation output analysis, Proceedings of the 23rd conference on Winter simulation, p.187-193, December 08-11, 1991, Phoenix, Arizona, United States
	John M. Charnes, Analyzing multivariate output, Proceedings of the 27th conference on Winter simulation, p.201-208, December 03-06, 1995, Arlington, Virginia, United States
	Kimmo E. E. Raatikainen, A sequential procedure for simultaneous estimation of several means, ACM Transactions on Modeling and Computer Simulation (TOMACS), v.3 n.2, p.108-133, April 1993
	John M. Charnes, Statistical analysis of output processes, Proceedings of the 25th conference on Winter simulation, p.41-49, December 12-15, 1993, Los Angeles, California, United States
	John M. Charnes, Power comparisons for the multivariate batch-means method, Proceedings of the 22nd conference on Winter simulation, p.281-287, December 09-12, 1990, New Orleans, Louisiana, United States
	Bruce W. Schmeiser , Wheyming Tina Song, Batching methods in simulation output analysis: what we know and what we don't, Proceedings of the 28th conference on Winter simulation, p.122-127, December 08-11, 1996, Coronado, California, United States
	Lori S. Cook, Factor screening of multiple responses, Proceedings of the 24th conference on Winter simulation, p.174-180, December 13-16, 1992, Arlington, Virginia, United States
	Krzysztof Pawlikowski, Steady-state simulation of queueing processes: survey of problems and solutions, ACM Computing Surveys (CSUR), v.22 n.2, p.123-170, June 1990