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

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  • Brandão, Rita Marques
  • Porta Nova, Acácio M.O.
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    Abstract

    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.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711010484
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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 218 (2012)
    Issue (Month): 3 ()
    Pages: 676-686

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    Handle: RePEc:eee:ejores:v:218:y:2012:i:3:p:676-686

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    Web page: http://www.elsevier.com/locate/eor

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    Keywords: Simulation; Time series; Stochastic processes;

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    1. Rob J. Hyndman & Yeasmin Khandakar, . "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, American Statistical Association, vol. 27(i03).
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