Analysis of event-based, single-server nonstationary simulation responses using classical time-series models

In this article, we present a metamodeling methodology for analyzing event-based, single-server nonstationary simulation responses that is based on the use of classical ARIMA (or SARIMA) time-series models. Some analytical results are derived for a Markovian queue and are used to evaluate the proposed methodology. The use of the corresponding procedure is illustrated on a traffic example from the simulation literature. Some conclusions are drawn and recommendations for further work are stated.

► We analyze event-based, single-server nonstationary simulation responses. ► Our approach is based on the use of classical ARIMA (or SARIMA) time-series models. ► We present unbiased estimators for the time spent in the system, or in the queue. ► Analytical results for a nonstationary M/M/1 queue derived to evaluate the approach. ► Linear and oscillatory responses are keenly captured by our approach.