IDEAS home Printed from https://ideas.repec.org/a/bpj/mcmeap/v13y2008i5-6p467-483n7.html
   My bibliography  Save this article

A use of algorithms for numerical modeling of order statistics

Author

Listed:
  • Voytishek Anton

    (Institute of Computational Mathematics and Mathematical Geophysics SD RAS, Lavrentieva 6, 630090 Novosibirsk, Russia. Email: vav@osmf.sscc.ru)

  • Myasnikov Alexandr
  • Saneev Leonid

    (Department of Mechanics and Mathematics, Novosibirsk State University, Pirogova 2, Novosibirsk, Russia.)

Abstract

In this paper a modification of the standard algorithm for the order statistics modeling, tied with the usage of confidence intervals is proposed. A study of applications of the standard algorithm for the order statistics modeling leads us to a conclusion that one of these applications (namely, the modeling of beta-distribution with integer parameters) gives the most effective algorithm for the order statistics modeling. A possibility to use the constructed algorithms in numerical modeling of random variables with polynomial distribution, as well as the beta-distribution with non-integer parameters, is shown.

Suggested Citation

  • Voytishek Anton & Myasnikov Alexandr & Saneev Leonid, 2008. "A use of algorithms for numerical modeling of order statistics," Monte Carlo Methods and Applications, De Gruyter, vol. 13(5-6), pages 467-483, January.
    • Handle: RePEc:bpj:mcmeap:v:13:y:2008:i:5-6:p:467-483:n:7
    DOI: 10.1515/mcma.2007.024
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/mcma.2007.024
    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.2007.024?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.

    References listed on IDEAS

    as
    1. Voytishek A. V., 1998. "Rejection methods for modelling of beta-distribution," Monte Carlo Methods and Applications, De Gruyter, vol. 4(1), pages 73-86, December.
    Full references (including those not matched with items on IDEAS)

    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.

      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:bpj:mcmeap:v:13:y:2008:i:5-6:p:467-483:n:7. 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: 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.