Confidence intervals using orthonormally weighted standardized time series

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Confidence intervals using orthonormally weighted standardized time series

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ACM Transactions on Modeling and Computer Simulation (TOMACS) archive
Volume 9 , Issue 4 (October 1999) table of contents

Pages: 297 - 325

Year of Publication: 1999

ISSN:1049-3301

Authors

Robert D. Foley	Georgia Institute of Technology, Atlanta
David Goldsman	Georgia Institute of Technology, Atlanta

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 10, Downloads (12 Months): 41, Citation Count: 9

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ABSTRACT

We extend the standardized time series area method for constructing confidence intervals for the mean of a stationary stochastic process. The proposed intervals are based on orthonormally weighted standardized time series area variance estimators. The underlying area estimators possess two important properties: they are first-order unbiased, and they are asymptotically independent of each other. These properties are largely the result of a careful choice of weighting functions, which we explicitly describe. The asymptotic independence of the area estimators yields more degrees of freedom than various predecessors; this, in turn, produces smaller mean and variance of the length of the resulting confidence intervals. We illustrate the efficacy of the new procedure via exact and Monte Carlo examples. We also provide suggestions for efficient implementation of the method.

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.

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CITED BY 9

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	Christos Alexopoulos , Seong-Hee Kim, Review of advanced methods for simulation output analysis, Proceedings of the 37th conference on Winter simulation, December 04-07, 2005, Orlando, Florida
	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
	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.
	James M. Calvin , Marvin K. Nakayama, Permuted weighted area estimators, Proceedings of the 36th conference on Winter simulation, December 05-08, 2004, Washington, D.C.
	Tûba Aktaran-Kalayci , David Goldsman , James R. Wilson, Confidence interval estimation using linear combinations of overlapping variance estimators, Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, December 09-12, 2007, Washington D.C.
	Christos Alexopoulos, Statistical analysis of simulation output: state of the art, Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, December 09-12, 2007, Washington D.C.
	Claudia Antonini , Christos Alexopoulos , David Goldsman , James R. Wilson, Folded standardized time series area variance estimators for simulation, Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, December 09-12, 2007, Washington D.C.
	Wheyming Tina Song , Mingchang Chih, Implementable mse-optimal dynamic partial-overlapping batch means estimators for steady-state simulations, Proceedings of the 40th Conference on Winter Simulation, December 07-10, 2008, Miami, Florida