Input Distribution Modeling Using the Kotlin Simulation Library

Input distribution modeling is an important aspect of stochastic simulation models. This paper provides an overview of the functionality of the discrete and continuous distribution modeling capabilities provided by the Kotlin Simulation Library (KSL). The library provides an API framework for defining distribution selection metrics, combining the metrics into an overall score, and recommending a distribution based on the scoring models. In addition, the library provides capabilities for performing goodness of fit statistical tests and other model fit diagnosis analyses. The paper provides context for how users can use existing capabilities and extend those capabilities to their needs. Examples are provided to illustrate the library.