| ExpertFit: total support for simulation input modeling |
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Winter Simulation Conference
archive
Proceedings of the 27th conference on Winter simulation
table of contents
Arlington, Virginia, United States
Pages: 395 - 400
Year of Publication: 1995
ISBN:0-7803-3018-8
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Authors
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Stephen Vincent
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Averill M. Law & Associates, P.O. Box 40996, Tucson, Arizona
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Averill M. Law
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Averill M. Law & Associates, P.O. Box 40996, Tucson, Arizona
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IEEE Computer Society
Washington, DC, USA
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Downloads (6 Weeks): 3, Downloads (12 Months): 7, Citation Count: 3
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ABSTRACT
We explain the important role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of ExpertFit, the Windows based successor to the UniFit II input modeling package. We use a set of real world system data to demonstrate how the package automatically specifies, evaluates, and ranks candidate probability distributions, and then assists an analyst in deciding whether the "best" candidate probability distribution provides an adequate representation of the data. If no candidate probability distribution provides an adequate fit, then ExpertFit can define an empirical distribution function. In either case, the probability distribution can be automatically expressed in the analyst's simulation software. We then consider the general case of selecting a probability distribution in the absence of data. As an example, we show how ExpertFit can be used to create busy time and downtime models for machines that are subject to random breakdowns.
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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Law, A.M., M.G. McComas, and S.G. Vincent. 1994. The Crucial Role of Input Modeling in Successful Simulation Studies. Industrial Engineering 26:55-59 (July 1994).
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