Analysis of simulation experiments by bootstrap resampling

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Analysis of simulation experiments by bootstrap resampling

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Winter Simulation Conference archive
Proceedings of the 33nd conference on Winter simulation table of contents

Arlington, Virginia

TUTORIAL SESSION: Advanced tutorials table of contents

Pages: 179 - 186

Year of Publication: 2001

ISBN:0-7803-7309-X

Author

Russell C. H. Cheng

University of Southampton, Southampton, SO17 1BJ, U.K.

Sponsors

INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
NIST : National Institute of Standards and Technology
ACM: Association for Computing Machinery
SCS : The Society for Computer Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association

Publisher

IEEE Computer Society Washington, DC, USA

Bibliometrics

Downloads (6 Weeks): 9, Downloads (12 Months): 27, Citation Count: 4

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ABSTRACT

This tutorial considers some very general procedures for analysing the results of a simulation experiment using bootstrap resampling. Bootstrapping has come to be recognised in statistics as being far ranging and effective. However it is not so well known in simulation despite being ideally suited for use in such a context. We discuss aspects ranging from the elementary to the advanced. We describe the rationale and the simple steps needed to implement bootstrapping in (i) estimation of the distributional properties of the output and its dependence on factors of interest; (ii) model fitting; (iii) model selection; (iv) model validation; (v) sensitivity analysis.

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 based on stochastic processes, Annals of Mathematical Statistics, 23: 193-212.
	2	Cheng, R. C. H. and W. Holland. 1995. The effect of input parameters on the variability of simulation output. In UKSS95, Proceedings of the 2nd Conference of the UK Simulation Society, eds. R. C. H. Cheng and R. B. Pooley, 29-36. Edinburgh: Edinburgh University Reprographics Press.
	3	Russell C. H. Cheng, Bootstrap methods in computer simulation experiments, Proceedings of the 27th conference on Winter simulation, p.171-177, December 03-06, 1995, Arlington, Virginia, United States [doi>10.1145/224401.224459]
	4	Russell C. H. Cheng , Wayne Holland , Neil A. Hughes, Selection of input models using bootstrap goodness-of-fit, Proceedings of the 28th conference on Winter simulation, p.199-206, December 08-11, 1996, Coronado, California, United States [doi>10.1145/256562.256604]
	5	Cheng, R. C. H. and W. Holland. 1997. Sensitivity of computer simulation experiments to errors in input data. Journal of Statistical Computation and Simulation, 57: 219-241.
	6	Chernick, M. R. 1999. Bootstrap Methods A Practitioner's Guide. New York, Wiley.
	7	Davison, A. C. and D. V. Hinkley. 1997. Bootstrap Methods and Their Application. Cambridge: Cambridge University Press.
	8	Efron, B. and R. J. Tibshirani. 1993. An Introduction to the Bootstrap. New York and London: Chapman & Hall.
	9	Helton, J. C. 1993. Uncertainty and Sensitivity Analysis Techniques for Use in Performance Assessment for Radioactive Waste Disposal. Reliability Engineering and System Safety, 42: 327-367.
	10	Helton, J. C. 1994. Treatment of Uncertainty in Performance Assessments for Complex Systems. Risk Analysis, 14: 483-511.
	11	Hjorth, J. S. U. 1994. Computer Intensive Statistical Methods. London: Chapman & Hall.
	12	Jack P. C. Kleijnen , Russell C. H. Cheng , Bert Bettonvil, Validation of Trace-Driven Simulation Models: Bootstrap Tests, Management Science, v.47 n.11, p.1533-1538, November 2001 [doi>10.1287/mnsc.47.11.1533.10255]

CITED BY 4

	Russell R. Barton , Stephen E. Chick , Russell C. H. Cheng , Shane G. Henderson , Averill M. Law , Bruce W. Schmeiser , Lawrence M. Leemis , Lee W. Schruben , James R. Wilson, Panel discussion on current issues in input modeling: panel on current issues in simulation input modeling, Proceedings of the 34th conference on Winter simulation: exploring new frontiers, December 08-11, 2002, San Diego, California
	Shane G. Henderson, Input modeling: input model uncertainty: why do we care and what should we do about it?, Proceedings of the 35th conference on Winter simulation: driving innovation, December 07-10, 2003, New Orleans, Louisiana
	Lance E. Champagne , Raymond R. Hill, Simulation validation with historic outcomes, Proceedings of the 37th conference on Winter simulation, December 04-07, 2005, Orlando, Florida
	Lance E. Champagne , Raymond R. Hill, Agent-model validation based on historical data, Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, December 09-12, 2007, Washington D.C.