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Statistical issues in simulation
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Source Winter Simulation Conference archive
Proceedings of the 28th conference on Winter simulation table of contents
Coronado, California, United States
Pages: 47 - 54  
Year of Publication: 1996
ISBN:0-7803-3383-7
Author
W. David Kelton  Department of Quantitative Analysis and Operations Management, College of Business Administration, University of Cincinnati, Cincinnati, Ohio
Sponsors
INFORMS/CS : Computer Science TC
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation
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
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 26,   Citation Count: 3
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ABSTRACT

This paper describes, in general terms, methods to help design the runs for simulation models and in terpreting their output. Statistical methods are described for several different purposes, and related problems like comparison, variance reduction, sensitivity estimation, metamodeling, and optimization are mentioned. The main point is to call attention to the challenges and opportunities in using simulation models carefully and effectively.


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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Banks, J. and J.S. Carson, II. 1984. Discrete-event system simulation. Englewood Cliffs, New Jersey: Prentice-Hall.
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Khoshnevis, B. 1994. Discrete systems szmulation. New York: McGraw-Hill.
 
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