An R library for validation of simulation models

Validation is an important phase in simulation that helps to evaluate models quality. Specifically, in continuous simulation models, real data and models results are compared. In this paper we present a library of methods to validate continuous simulation models that facilitate this task. We included several of the most used models validation techniques: from simple index such as mean squared error and its variants (Theil statistics, model efficiency, etc.) to classical statistical methods (model vs data regressions, paired t-test and others). We also included Bayesian statistical methods and information criteria methods that allow choosing between different models. The library includes several data frames, help and a manual for better understanding of the techniques and its application. The library was developed in R language and is available.