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Expert fit: how the ExpertFit distribution-fitting package can make your simulation models more valid
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Source Winter Simulation Conference archive
Proceedings of the 32nd conference on Winter simulation table of contents
Orlando, Florida
TUTORIAL SESSION: Software/modelware tutorials II table of contents
Pages: 253 - 258  
Year of Publication: 2000
ISBN:0-7803-6582-8
Authors
Averill M. Law  Averill M. Law and Associates, Inc., Tucson, AZ
Michael G. McComas  Averill M. Law and Associates, Inc., Tucson, AZ
Sponsors
IIE : Institute of Industrial Engineers
ASA : American Statistical Association
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
INFORMS-CS : Institute for Operations Research and the Management Sciences-College on Simulation
NIST : National Institute of Standards and Technology
SIGSIM: ACM Special Interest Group on Simulation and Modeling
SCS : The Society for Computer Simulation International
Publisher
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 22,   Citation Count: 0
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ABSTRACT

In this paper, we discuss the critical 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 the ExpertFit distribution-fitting software. We use a set of real-world data to demonstrate how the software automatically specifies and ranks probability distributions, and then tells the analyst whether the "best" candidate distribution is actually a good representation of the data. If no distribution provides a good fit, then ExpertFit can define an empirical distribution. In either case, the selected distribution is put into the proper format for direct input to the analyst's simulation software.


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Collaborative Colleagues:
Averill M. Law: colleagues
Michael G. McComas: colleagues