IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v66y2004i4p861-875.html
   My bibliography  Save this article

Nonparametric inference about service time distribution from indirect measurements

Author

Listed:
  • Peter Hall
  • Juhyun Park

Abstract

Summary. In studies of properties of queues, for example in relation to Internet traffic, a subject that is of particular interest is the ‘shape’ of service time distribution. For example, we might wish to know whether the service time density is unimodal, suggesting that service time distribution is possibly homogeneous, or whether it is multimodal, indicating that there are two or more distinct customer populations. However, even in relatively controlled experiments we may not have access to explicit service time data. Our only information might be the durations of service time clusters, i.e. of busy periods. We wish to ‘deconvolve’ these concatenations, and to construct empirical approximations to the distribution and, particularly, the density function of service time. Explicit solutions of these problems will be suggested. In particular, a kernel‐based ‘deconvolution’ estimator of service time density will be introduced, admitting conventional approaches to the choice of bandwidth.

Suggested Citation

  • Peter Hall & Juhyun Park, 2004. "Nonparametric inference about service time distribution from indirect measurements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 861-875, November.
    • Handle: RePEc:bla:jorssb:v:66:y:2004:i:4:p:861-875
    DOI: 10.1111/j.1467-9868.2004.B5725.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9868.2004.B5725.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9868.2004.B5725.x?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
    ---><---

    References listed on IDEAS

    as
    1. N.H. Bingham & Bruce Dunham, 1997. "Estimating Diffusion Coefficients From Count Data: Einstein-Smoluchowski Theory Revisited," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(4), pages 667-679, December.
    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. Schweer, Sebastian & Wichelhaus, Cornelia, 2015. "Nonparametric estimation of the service time distribution in the discrete-time GI/G/∞ queue with partial information," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 233-253.
    2. Park, Juhyun, 2007. "On the choice of an auxiliary function in the M/G/[infinity] estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5477-5482, August.
    3. Martin Bøgsted & Susan Pitts, 2010. "Decompounding random sums: a nonparametric approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(5), pages 855-872, October.
    4. Aleksandrina Goeva & Henry Lam & Huajie Qian & Bo Zhang, 2019. "Optimization-Based Calibration of Simulation Input Models," Operations Research, INFORMS, vol. 67(5), pages 1362-1382, September.
    5. Li, Dongmin & Hu, Qingpei & Wang, Lujia & Yu, Dan, 2019. "Statistical inference for Mt/G/Infinity queueing systems under incomplete observations," European Journal of Operational Research, Elsevier, vol. 279(3), pages 882-901.
    6. Azam Asanjarani & Yoni Nazarathy & Peter Taylor, 2021. "A survey of parameter and state estimation in queues," Queueing Systems: Theory and Applications, Springer, vol. 97(1), pages 39-80, February.

    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. Peter Whittle, 2002. "Applied Probability in Great Britain," Operations Research, INFORMS, vol. 50(1), pages 227-239, February.
    2. N. Bingham & Susan Pitts, 1999. "Non-parametric Estimation for the M/G/∞ Queue," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(1), pages 71-97, March.

    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:bla:jorssb:v:66:y:2004:i:4:p:861-875. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.