In this paper 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 UniFit II. 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 UniFit II can define art empirical distribution function. In either case, the probability model 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 UnFit II can be used to create busy-time and downtime models for machines that are subject to random breakdowns.
['Stephen G. Vincent']
UniFit II: total support for simulation input modeling