IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v52y2008i3p1615-1635.html
   My bibliography  Save this article

Bayesian prediction of the transient behaviour and busy period in short- and long-tailed GI/G/1 queueing systems

Author

Listed:
  • Ausin, M. Concepcion
  • Wiper, Michael P.
  • Lillo, Rosa E.

Abstract

No abstract is available for this item.

Suggested Citation

  • Ausin, M. Concepcion & Wiper, Michael P. & Lillo, Rosa E., 2008. "Bayesian prediction of the transient behaviour and busy period in short- and long-tailed GI/G/1 queueing systems," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1615-1635, January.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:3:p:1615-1635
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(07)00211-3
    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. Robert, Christian P. & Mengersen, Kerrie L., 1999. "Reparameterisation Issues in Mixture Modelling and their bearing on MCMC algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 29(3), pages 325-343, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. M. Concepcion Ausin & Michael P. Wiper & Rosa E. Lillo, 2009. "Bayesian estimation of finite time ruin probabilities," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(6), pages 787-805, November.
    2. Lin, Lei & Wang, Qian & Sadek, Adel W., 2014. "Border crossing delay prediction using transient multi-server queueing models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 65-91.
    3. McGrory, C.A. & Pettitt, A.N. & Faddy, M.J., 2009. "A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4311-4321, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008. "Parameterisation and efficient MCMC estimation of non-Gaussian state space models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2911-2930, February.
    2. L. Bauwens & J. V. K. Rombouts, 2007. "Bayesian Clustering of Many Garch Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 365-386.
    3. Palacios, Ana Paula & Marín Díazaraque, Juan Miguel & Quinto, Emiliano & Wiper, Michael Peter, 2012. "Bayesian modelling of bacterial growth for multiple populations," DES - Working Papers. Statistics and Econometrics. WS ws121610, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Luc Bauwens & Jeroen Rombouts, 2004. "Bayesian Clustering Of Similar Multivariate Garch Models," Econometric Society 2004 North American Winter Meetings 370, Econometric Society.
    5. Cai, Bo & Meyer, Renate, 2011. "Bayesian semiparametric modeling of survival data based on mixtures of B-spline distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1260-1272, March.
    6. Perrakis, Konstantinos & Ntzoufras, Ioannis & Tsionas, Efthymios G., 2014. "On the use of marginal posteriors in marginal likelihood estimation via importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 54-69.

    More about this item

    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:csdana:v:52:y:2008:i:3:p:1615-1635. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.