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Analysis of event-based, single-server nonstationary simulation responses using classical time-series models. (English) Zbl 1244.90063
Summary: 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.
MSC:
90B22 Queues and service in operations research
60K25 Queueing theory (aspects of probability theory)
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
90B20 Traffic problems in operations research
Software:
forecast; Forecast
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References:
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