Input Modeling When Simple Models Fail

Abstract

A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncertain elements. Simple input models, consisting of independent and identically distributed sequences of random variates from standard probability distributions, are included in every commercial simulation language. Software to fit these distributions to data is also available. In this tutorial we describe input models that are useful when simple models are not.

DOI: 10.1145/224401.224429

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Cite this paper

@inproceedings{Nelson1995InputMW, title={Input Modeling When Simple Models Fail}, author={Barry L. Nelson and Marne C. Cario and Chester A. Harris and Stephanie A. Jamison and John O. Miller and James Steinbugl and Jaehwan Yang and Peter P. Ware}, booktitle={Winter Simulation Conference}, year={1995} }