Non-stationary queue simulation analysis using time series

In this work, we extend the use of time series models to the output analysis of non-stationary discrete event simulations. In particular, we investigate and experimentally evaluate the applicability of ARIMA(p, d, q) models as potential meta-models for simulating queueing systems under critical traffic conditions. We exploit stationarity-inducing transformations, in order to efficiently estimate performance measures of selected responses in the system under study.