Simulation output analysis

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Simulation output analysis

Full text

Pdf (675 KB)

Source

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

Arlington, Virginia, United States

Pages: 97 - 103

Year of Publication: 1992

ISBN:0-7803-0798-4

Author

David Goldsman

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

Bibliometrics

Downloads (6 Weeks): 7, Downloads (12 Months): 34, Citation Count: 8

Additional Information:

references cited by index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/167293.167310 What is a DOI?

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	Banks, J., and J. S. Carson, II. 1984. Discrete-event system simulation. Englewood Cliffs, New Jersey: Prentice-Hall.
	2	Banks, J., J. S. Carson, II, and D. Goldsman. 1990. Computer simulation. In Handbook of statistical methods for engineers and scientists, ed. H. M. Wadsworth, 12.1-12.36. New York: McGraw-Hill.
	3	Paul Bratley , Bennett L. Fox , Linus E. Schrage, A guide to simulation (2nd ed.), Springer-Verlag New York, Inc., New York, NY, 1987
	4	Chance, F., and L. W. Schruben. 1992. Establishing a truncation point in simulation output. Technical Report, School of Operations Research and Industrial Engineering, Cornell University, ithaca, New York.
	5	Crane, M. A., and D. L. Iglehart. 1975. Simulating stable stochastic systems: III. regenerative processes and discrete-event simulations. Operations Research 23:33-45.
	6	A. A. Crane , J. Lemoine, An Introduction to the Regenerative Method for Simulation Analysis, Springer-Verlag New York, Inc., Secaucus, NJ, 1977
	7	George S. Fishman, Principles of Discrete Event Simulation, John Wiley & Sons, Inc., New York, NY, 1978
	8	Gafarian, A. V., C. J. Ancker, Jr., and T. Morisaku. 1978. Evaluation of commonly used rules for detecting 'steady state' in computer simulation. Naval Research Logistics Quarterly 25:511-529.
	9	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]
	10	Ooldsman, D., and L. W. Schruben. 1984. Asymptotic properties of some confidence interval estimators for simulation output. Management Science 30:1217-1225.
	11	Goldsman, D., L. W. Schruben, and J. J. Swain. 1990. Tests for transient means in simulated time series. Technical Report, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia.
	12	Philip Heidelberger , Peter D. Welch, A spectral method for confidence interval generation and run length control in simulations, Communications of the ACM, v.24 n.4, p.233-245, April 1981 [doi>10.1145/358598.358630]
	13	Heidelberger, P., and P. D. Welch. 1983. Simulation run length control in the presence of an intial transient. Operations Research 31:1109-1144.
	14	Sarah J. Hood , Peter D. Welch, Experimental design issues in simulation with examples from semiconductor manufacturing, Proceedings of the 24th conference on Winter simulation, p.255-263, December 13-16, 1992, Arlington, Virginia, United States [doi>10.1145/167293.167346]
	15	Kelton, W. D., and A. M. Law. 1983. A new approach for dealing with the startup problem in discrete event simulation. Naval Research Logistics Quarterly 30:641-658.
	16	Law, A. M., and W. D. Kelton. 1984. Confidence intervals for steady-state simulations, I: a surw.~y of fixed sample size procedures. Operations Research 32:1221-1239.
	17	Averill M. Law , W. David Kelton, Simulation Modeling and Analysis, McGraw-Hill Higher Education, 1997
	18	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
	19	Barry L. Nelson, Designing efficient simulation experiments, Proceedings of the 24th conference on Winter simulation, p.126-132, December 13-16, 1992, Arlington, Virginia, United States [doi>10.1145/167293.167317]
	20	Sargent, R. G. 1979. An introduction to statistical analysis of simulation output data. In Proceedings of the 1979 A GARD Syrup. Paris, France.
	21	Robert G. Sargent , Keebom Kang , David Goldsman, An investigation of finite-sample behavior of confidence interval estimators, Operations Research, v.40 n.5, p.898-913, Sept.–Oct. 1992 [doi>10.1287/opre.40.5.898]
	22	Schmeiser, B.W. 1982. Batch size effects in, the analysis of simulation output. Operations Research 30:556-568.
	23	Schruben, L. W. 1982. Detecting initialization bias in simulation output. Operations Research 30:569- 590.
	24	Sehruben, L. W. 1983. Confidence interval estimation using standardized time series. Operations Research 31:1090-1108.
	25	Schruben, L. W., and D. Goldsman. 1985. Initialization effects in computer simulation experiments. Technical Report #594, School of Operations Research and Industrial Engineering, Cornell University, Ithaca, New York.
	26	Schruben, L. W., H. Singh, and L. Tierney. I983. Optimal tests for initialization bias in simulation output. Operations Research 31:1167-1178.
	27	Seila, A. F. 1992. Advanced Output Analysis TutoriM. In Proceedings of the 1992 Winter Simulation Conference (this volume).
	28	Welch, P. D. 1981. On the problem of the initial transient in steady state simulations. IBM Watson Research Center, Yorktown Heights, New York.
	29	Welch, P. D. 1983. The statistical analysis of simulation results. In The computer performance modeling handbook, ed. S. Lavenberg. Orlando, Florida: Academic Press.
	30	Wilson, J. R., and A. A. B. Pritsker. 1978a. A survey of research on the simulation startup problem. Simulation 31:55-58.
	31	Wilson, J. R., and A. A. B. Pritsker. 1978b. Evaluation of startup policies in simulation experiments. Simulation 31:79-89.

CITED BY 8

	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
	W. David Kelton, Statistical analysis of simulation output, Proceedings of the 29th conference on Winter simulation, p.23-30, December 07-10, 1997, Atlanta, Georgia, United States
	W. David Kelton, Analysis of output data, Proceedings of the 26th conference on Winter simulation, p.62-68, December 11-14, 1994, Orlando, Florida, United States
	Barry L. Nelson, Designing efficient simulation experiments, Proceedings of the 24th conference on Winter simulation, p.126-132, December 13-16, 1992, Arlington, Virginia, United States
	Martha A. Centeno , M. Florencia Reyes, So you have your model: what to do next. A tutorial on simulation output analysis, Proceedings of the 30th conference on Winter simulation, p.23-30, December 13-16, 1998, Washington, D.C., United States
	W. David Kelton, A tutorial on design and analysis of simulation experiments, Proceedings of the 27th conference on Winter simulation, p.24-31, December 03-06, 1995, Arlington, Virginia, United States
	David Goldsman , Gamze Tokol, Output analysis: output analysis procedures for computer simulations, Proceedings of the 32nd conference on Winter simulation, December 10-13, 2000, Orlando, Florida
	W. David Kelton, Statistical issues in simulation, Proceedings of the 28th conference on Winter simulation, p.47-54, December 08-11, 1996, Coronado, California, United States