IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v218y2012i3p676-686.html
   My bibliography  Save this article

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

Author

Listed:
  • Brandão, Rita Marques
  • Porta Nova, Acácio M.O.

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.

Suggested Citation

  • Brandão, Rita Marques & Porta Nova, Acácio M.O., 2012. "Analysis of event-based, single-server nonstationary simulation responses using classical time-series models," European Journal of Operational Research, Elsevier, vol. 218(3), pages 676-686.
  • Handle: RePEc:eee:ejores:v:218:y:2012:i:3:p:676-686
    DOI: 10.1016/j.ejor.2011.11.039
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711010484
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Simulation; Time series; Stochastic processes;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:218:y:2012:i:3:p:676-686. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eor .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.