Confidence intervals and orthonormally weighted standardized time series

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Confidence intervals and orthonormally weighted standardized time series

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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: 422 - 424

Year of Publication: 1988

ISBN:0-911801-42-1

Authors

Robert D. Foley	School of ISyE, Georgia Tech Atlanta, Georgia
David Goldsman	School of ISyE, Georgia Tech, Atlanta, Georgia

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): 4, Downloads (12 Months): 7, Citation Count: 4

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ABSTRACT

We find new confidence intervals for the mean of a stationary process. The new intervals are based on orthonormally weighted standardized time series and asymptotically have smaller half-length mean and variance than their predecessors.

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	R. D. Foley and D. Goldsman, ~Confidence Intervals Using Orthonormally Weighted Standardized Time Series," Technical Report, School of Industrial and Systems Engineering, Georgia institute of Technology, Atlanta, Georgia (1088).
	2	P. Glynn and D. L. Iglehart, "The Theory of Standardized Time Series," Technical Report ~32, Department of Operations Research, Stanford University, Stanford, California (1985).
	3	D. Goldsman and L. Schruben, "New Confidence Internical Report ~J-84-15, School of Industrial and Systerr~ Engineering, Georgia Institute of Technology, Atlanta, Georgia (1986).
	4	L. Schruben, "Confidence Interval Estimation Using Standardized Time Series," Operations Research 31, 1090--1108 (1083).

CITED BY 4

	Antonio C. Pedrosa , Bruce W. Schmeiser, Asymptotic and finite-sample correlations between OBM estimators, Proceedings of the 25th conference on Winter simulation, p.481-488, December 12-15, 1993, Los Angeles, California, United States
	Wheyming Tina Song , Neng-Hui Shih , Mingjian Yuan, Optimal quadratic-form estimator of the variance of the sample mean, Proceedings of the 29th conference on Winter simulation, p.246-252, December 07-10, 1997, Atlanta, Georgia, United States
	Robert D. Foley , David Goldsman, Confidence intervals using orthonormally weighted standardized time series, ACM Transactions on Modeling and Computer Simulation (TOMACS), v.9 n.4, p.297-325, Oct. 1999
	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