IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v58y2002i1p93-96.html
   My bibliography  Save this article

On fractional uniform order statistics

Author

Listed:
  • Jones, M. C.

Abstract

The fractional uniform order statistics of Stigler [J. Amer. Statist. Assoc. 72 (1977) 544] are shown to correspond to a randomised version of the alternative fractional uniform order statistics defined by taking convex combinations of consecutive uniform order statistics.

Suggested Citation

  • Jones, M. C., 2002. "On fractional uniform order statistics," Statistics & Probability Letters, Elsevier, vol. 58(1), pages 93-96, May.
  • Handle: RePEc:eee:stapro:v:58:y:2002:i:1:p:93-96
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(02)00119-0
    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. Alan Hutson, 1999. "Calculating nonparametric confidence intervals for quantiles using fractional order statistics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(3), pages 343-353.
    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. Beutner, E. & Cramer, E., 2014. "Using linear interpolation to reduce the order of the coverage error of nonparametric prediction intervals based on right-censored data," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 95-109.
    2. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.
    3. David M. Kaplan & Matt Goldman, 2011. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri, revised 21 Nov 2016.
    4. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    5. Beutner, Eric & Kamps, Udo, 2007. "Random convex combinations of order statistics," Statistics & Probability Letters, Elsevier, vol. 77(11), pages 1133-1136, June.

    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:stapro:v:58:y:2002:i:1:p:93-96. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.