A new variance-reduction technique for regenerative simulations of Markov chains

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A new variance-reduction technique for regenerative simulations of Markov chains

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Winter Simulation Conference archive
Proceedings of the 29th conference on Winter simulation table of contents

Atlanta, Georgia, United States

Pages: 224 - 229

Year of Publication: 1997

ISBN:0-7803-4278-X

Authors

James M. Calvin	Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ
Marvin K. Nakayama	Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ

Sponsors

IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
INFORMS/CS : Computer Science TC
SIGSIM: ACM Special Interest Group on Simulation and Modeling
SCS : Society for Computer Simulation
ASA : American Statistical Association
IEEE : Institute of Electrical and Electronics Engineers

Publisher

IEEE Computer Society Washington, DC, USA

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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	Calvin, J. M. and M. K. Ntiyama. 1997. A new variance-reduction technique for regenerative simulations. Research Report CIS-97-16. Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ.
	2	Crane, M. and D. L. Iglehart. 1975. Simulating stable stochastic systems, III: Regenerative processes and discrete-event simulations. Operations Research 23:33-45.
	3	Glynn, P. W. and D. L. Iglehart. 1987. A joint central liiit theorem for the sample mean and regenerative variance estimator. Annals of Opemtions Research 8:41-55.
	4	Shedler, G. S. 1993. Regenemtive Stochastic Simulation. San Diego: Academic Press.