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Expertfit: Total Support for Simulation Input Modeling the Role of Simulation Input Modeling in a Successful Simulation Study 1.2 Two Pitfalls in Simulation Input Modeling 1.2.1 Pitfall Number 1: Replacing a Distribution by Its Mean
| Content Provider | Semantic Scholar |
|---|---|
| Author | Farrington, Phillip A. Nembhard, Harriet Black Sturrock, David T. Evans, Gerald W. |
| Copyright Year | 1999 |
| Abstract | In this paper, we discuss the critical role of simulati input modeling in a successful simulation study. Tw pitfalls in simulation input modeling are then presented a we explain how any analyst, regardless of their knowled of statistics, can easily avoid these pitfalls through the of the ExpertFit distribution-fitting software. We use a s of real-world data to demonstrate how the softwa automatically specifies and ranks probability distribution and then assists the analyst in deciding whether the “b candidate distribution actually provides a goo representation of the data. If no distribution provides good fit, then ExpertFit can define an empiric distribution. In either case, the selected distribution is into the proper format for direct input to the analyst simulation software. We then consider the case of selec a distribution in the absence of data. As an example, show how ExpertFit can be used to specify time-to-failu and repair-time distributions for a machine that is subj to random downtimes. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.informs-sim.org/wsc99papers/036.PDF |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
