[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v48y1999i3p377-394.html
   My bibliography  Save this article

Parameter Estimation in Large Dynamic Paired Comparison Experiments

Author

Listed:
  • Mark E. Glickman
Abstract
Paired comparison data in which the abilities or merits of the objects being compared may be changing over time can be modelled as a non‐linear state space model. When the population of objects being compared is large, likelihood‐based analyses can be too computationally cumbersome to carry out regularly. This presents a problem for rating populations of chess players and other large groups which often consist of tens of thousands of competitors. This problem is overcome through a computationally simple non‐iterative algorithm for fitting a particular dynamic paired comparison model. The algorithm, which improves over the commonly used algorithm of Elo by incorporating the variability in parameter estimates, can be performed regularly even for large populations of competitors. The method is evaluated on simulated data and is applied to ranking the best chess players of all time, and to ranking the top current tennis‐players.

Suggested Citation

  • Mark E. Glickman, 1999. "Parameter Estimation in Large Dynamic Paired Comparison Experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(3), pages 377-394.
    • Handle: RePEc:bla:jorssc:v:48:y:1999:i:3:p:377-394
    DOI: 10.1111/1467-9876.00159
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9876.00159
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-9876.00159?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
    ---><---

    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:jorssc:v:48:y:1999:i:3:p:377-394. 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: 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.