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Introduction to modeling and generating probabilistic input processes for simulation

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5 Author(s)
Michael E. Kuhl ; Industrial & Systems Engineering Department Rochester Institute of Technology, NY 14623, U.S.A. ; Natalie M. Steiger ; Emily K. Lada ; Mary Ann Wagner
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Techniques are presented for modeling and generating the univariate probabilistic input processes that drive many simulation experiments. Emphasis is on the generalized beta distribution family, the Johnson translation system of distributions, and the Bezier distribution family. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogeneous Pois- son processes. Public-domain software implementations and current applications are presented for each input-modeling technique. Many of the references include live hyperlinks providing online access to the referenced material.

Published in:

2007 Winter Simulation Conference

Date of Conference:

9-12 Dec. 2007