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Gradient estimation for regenerative processes
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Source Winter Simulation Conference archive
Proceedings of the 24th conference on Winter simulation table of contents
Arlington, Virginia, United States
Pages: 280 - 288  
Year of Publication: 1992
ISBN:0-7803-0798-4
Authors
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
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Downloads (6 Weeks): 3,   Downloads (12 Months): 11,   Citation Count: 4
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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
Asmussen, S. 1987. Applied Probability and Queues, New York: Wiley.
 
2
Glasserman, P. 1992a. Regenerative Derivatives of Regenerative Sequences. Adv. Appl. Prob., to appear.
 
3
 
4
Glasserman, P., J.Q. Hu, and S.G. Strickland. 1991. Strongly Consistent Steady-State Derivative Estimates. Prob. Inf. Eng. Sci. 5:391-413.
 
5
Glynn, P.W. (1989). A GSMP Formalism for Discrete Event Systems. Proc. IEEE 77:1423.
 
6
Hu, J.Q. 1992. Convexity of Sample Path Performances and Strong Consistency of Infinitesimal Perturbation Analysis. IEEE Trans. Automatic Control 37:258-262.
 
7
Meyn, S.P., and R.L. Tweedie. 1992. Markov chains and Stochastic Stability, Springer-Verlag, New York.


Collaborative Colleagues:
Paul Glasserman: colleagues
Peter W. Glynn: colleagues

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