Asymptotic and finite-sample correlations between OBM estimators

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Asymptotic and finite-sample correlations between OBM estimators

Full text

Pdf (547 KB)

Source

Winter Simulation Conference archive
Proceedings of the 25th conference on Winter simulation table of contents

Los Angeles, California, United States

Pages: 481 - 488

Year of Publication: 1993

ISBN:0-7803-1381-X

Authors

Antonio C. Pedrosa	School of Industrial Engineering, Purdue University, West Lafayette, IN
Bruce W. Schmeiser	School of Industrial Engineering, Purdue University, West Lafayette, IN

Sponsors

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
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation
ASA : American Statistical Association
NIST : National Institue of Standards & Technology
TIMS/CSG :

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 0, Downloads (12 Months): 10, Citation Count: 8

Additional Information:

references cited by 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/10.1145/256563.256692 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	Anderson, T. W. 1971. Analysis of Time Series. New York: John Wiley & Sons.
	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	Robert D. Foley , David Goldsman, Confidence intervals and orthonormally weighted standardized time series, Proceedings of the 20th conference on Winter simulation, p.422-424, December 12-14, 1988, San Diego, California, United States [doi>10.1145/318123.318227]
	4	Hannan, E. J. 1957. The variance of the mean of a stationary process. Journal of the Royal Statistical Society, B 19:282-285.
	5	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]
	6	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
	7	Moran, P. A. P. 1975. The estimation of standard errors in Monte Carlo simulation experiments. Biometrika, 62:1-4.
	8	Pedrosa, A. C., and B. W. Schmeiser. 1993a. The d-State Bernoulli-Demand (s, S)-Inventory Markov Chain. School of Industrial Engineering, Purdue University, West Lafayette, Indiana.
	9	Pedrosa, A. C., and B. W. Schmeiser. 1993b. Asymptotic covariance between Bartlett estimators of the spectral density. Working Paper. School of Industrial Engineering, Purdue University, West Lafayette, Indiana.
	10	Politis, D. N. and J. P. Romano. 1992. Bias- Corrected Nonparametric Spectral Estimation. Technical Report 92-50, Department of Statistics, Purdue University, West Lafayette, Indiana.
	11	Schmeiser, B. W. 1982. Batch size effects in the analysis of simulation output. Operations Research, 30:556-568.
	12	Schmeiser, B. W., and W.-M. T. Song. 1989. Optimal mean-squared-error batch sizes. Technical Report 89-3, School of Industrial Engineering, Purdue University, West Lafayette, Indiana.
	13	Schruben, L. W. 1983. Confidence interval estimation using standardized time series. Operations Research, 31:1090-1108.
	14	Song, W.-M. T., and B. W. Schmeiser. 1988a. On the dispersion matrix of variance estimators of the sample mean in the analysis of simulation output. Operations Research Letters, 7:259-266.
	15	Wheyming Tina Song , Bruce Schmeiser, Minimal-MSE linear combinations of variance estimators of the sample mean, Proceedings of the 20th conference on Winter simulation, p.414-421, December 12-14, 1988, San Diego, California, United States [doi>10.1145/318123.318226]
	16	Wheyming Tina Song , Bruce W. Schmeiser, Variance of the sample mean: properties and graphs of quadratic-form estimators, Operations Research, v.41 n.3, p.501-517, May/June 1993 [doi>10.1287/opre.41.3.501]

CITED BY 8

	Michael Sherman, On batch means in the simulation and statistics communities, Proceedings of the 27th conference on Winter simulation, p.297-302, December 03-06, 1995, Arlington, Virginia, United States
	Bruce Schmeiser, Simulation output analysis: a tutorial based on one research thread, Proceedings of the 36th conference on Winter simulation, December 05-08, 2004, Washington, D.C.
	Christos Alexopoulos , David Goldsman , Nilay Tanik Argon , Gamze Tokol, Overlapping variance estimators for simulations, Proceedings of the 36th conference on Winter simulation, December 05-08, 2004, Washington, D.C.
	Tûba Aktaran-Kalayci , David Goldsman, Linear combinations of overlapping variance estimators for simulations, Proceedings of the 37th conference on Winter simulation, December 04-07, 2005, Orlando, Florida
	David Goldsman , Bruce W. Schmeiser, Computational efficiency of batching methods, Proceedings of the 29th conference on Winter simulation, p.202-207, December 07-10, 1997, Atlanta, Georgia, United States
	David Goldsman , James O. Henriksen , Pierre L'Ecuyer , Barry L. Nelson , David H. Withers , Nilay Tanik Argon, Fortieth anniversary special panel: Landmark papers, Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, December 09-12, 2007, Washington D.C.
	David Goldsman , James O. Henriksen , Pierre L'Ecuyer , Barry L. Nelson , David H. Withers , Nilay Tanik Argon, Fortieth anniversary special panel: Landmark papers, Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, December 09-12, 2007, Washington D.C.
	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

Collaborative Colleagues:

Antonio C. Pedrosa: colleagues

Bruce W. Schmeiser: colleagues

Adobe Acrobat

QuickTime

Windows Media Player

Real Player