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Automated estimation and variance reduction for steady-state simulations
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Source Winter Simulation Conference archive
Proceedings of the 18th conference on Winter simulation table of contents
Washington, D.C., United States
Pages: 871 - 875  
Year of Publication: 1986
ISBN:0-911801-11-1
Authors
Rowena Añonuevo  Department of industrial and Systems Engineering, The Ohio State University, 1971 Neil Avenue, Columbus, Ohio
Barry L. Nelson  Department of industrial and Systems Engineering, The Ohio State University, 1971 Neil Avenue, Columbus, Ohio
Sponsor
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 8,   Citation Count: 2
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ABSTRACT

We present an automated procedure that interfaces with SIMSCRIPT II.5 simulation experiments to derive point and interval estimators for steady-state parameters of stochastic simulations. The procedure combines the nonoverlapping batch means method of output analysis and the control variates variance reduction technique. Batch size and control variates are selected automatically.


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
Anonuevo, M.R. (1986). Automated Estimation and Variance Reduction via Control Variates for SIMSCRIPT 11.5 Simulations. Unpublished M.S. thesis, Department of Industrial and Systems Engineering, The Ohio State University,
 
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3
Fishman, G.S. (1978), Grouping Observations in Digital Simulation, Management Science 24, 510-521.
 
4
Lavenberg, S.S. and P.D. Walch (1981). A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations. Management Science 27, 322-335.
 
5
Law, A.M. and J.S. Carson (1979). A Sequential Procedure for Determining the Length of a Steady State Simulation. Operation Rearch 27, 1011-1025.
 
6
Malkovich, J.F. and A.A. Afife (1973). On Tests for Multivariate Normality. Journal of the American Statistical Association 68, 176-179.
 
7
Mechanic, H. and W. McKay (1966). Confidence Intervals for Averages of Dependent Data in Simulations II. Technical Report ASDD 17-202, IBM Corp., Yorktown Heights, NY,
 
8
Nelson, B.L, (1986), Batch Size Effects on the Efficiency of Control Variates in Simulation. Working Paper Series No. 1986-001, Department of Industrial and Systems Engineering, The Ohio State University.
 
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10
Russell, E.C. (1983). Building Simulation Models with SIMSCRIPT II.5. C.A.C.L, Los Angeles.
 
11
Schmeiser, B. (1982), Batch Size Effects in the Analysis of Simulation Output, Operations Research 30, 556-568.
 
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13
Wilson, J.R., and A.A.B. Pritsker (1984a). Variance Reduction in Queueing Simulation using Generalized Concomitant Variables. Journal of Statistical Computation and Simulation 19, 129-153
 
14
Wilson, J.R. and A.A.B. Pritsker (1984b). Experimental Evaluation of Variance Reduction Techniques for Queueing Simulation using Generalized Concomitant Variables. Management, Science 30, 1459-1472.


Collaborative Colleagues:
Rowena Añonuevo: colleagues
Barry L. Nelson: colleagues