IDEAS home Printed from https://ideas.repec.org/a/bpj/mcmeap/v29y2023i4p351-366n2.html
   My bibliography  Save this article

Statistical analysis of the estimates of some stationary performances of the unreliable M/M/1/N queue with Bernoulli feedback

Author

Listed:
  • Nita Hadjer

    (Laboratory of Applied Mathematics, Mathematics Department, University of Biskra, 07000, Biskra, Algeria)

  • Afroun Faïrouz

    (Laboratory of Pure and Applied Mathematics, University of Tizi-Ouzou, 15000, Tizi-Ouzou, Algeria)

  • Cherfaoui Mouloud

    (Mathematics Department, University of Biskra, 07000, Biskra, ; and Research Unit LaMOS (Modeling and Optimization of Systems), University of Bejaia, 06000 Bejaia, Algeria)

  • Aïssani Djamil

    (Research Unit LaMOS (Modeling and Optimization of Systems), University of Bejaia, 06000, Bejaia, Algeria)

Abstract

In this work, we considered the parametric estimation of the characteristics of the M/M/1/N{M/M/1/N} waiting model with Bernoulli feedback. Through a Monte-Carlo simulation study, we have illustrated the effect of the estimation of the starting parameters of the considered waiting system on the statistical properties of its performance measures estimates, when these latter are obtained using the plug-in method. In addition, several types of convergence (bias, variance, MSE, in law) of these performance measure estimators have also been showed by simulation.

Suggested Citation

  • Nita Hadjer & Afroun Faïrouz & Cherfaoui Mouloud & Aïssani Djamil, 2023. "Statistical analysis of the estimates of some stationary performances of the unreliable M/M/1/N queue with Bernoulli feedback," Monte Carlo Methods and Applications, De Gruyter, vol. 29(4), pages 351-366, December.
  • Handle: RePEc:bpj:mcmeap:v:29:y:2023:i:4:p:351-366:n:2
    DOI: 10.1515/mcma-2023-2004
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/mcma-2023-2004
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.1515/mcma-2023-2004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:bpj:mcmeap:v:29:y:2023:i:4:p:351-366:n:2. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.