IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v61y2020i4d10.1007_s00362-018-0999-8.html
   My bibliography  Save this article

Cramér’s type results for some bootstrapped U-statistics

Author

Listed:
  • Sergio Alvarez-Andrade

    (Université de Technologie de Compiègne)

  • Salim Bouzebda

    (Université de Technologie de Compiègne)

Abstract

In the present paper, we are mainly interested in Cramér-type results for the weighted bootstrap of the U-statistics. The method of proof is based on the Hoeffding decomposition according to the bootstrapped Cramér transform together with the contraction technique. Finally, we investigate the U-statistics indexed by a one dimensional symmetric random walk.

Suggested Citation

  • Sergio Alvarez-Andrade & Salim Bouzebda, 2020. "Cramér’s type results for some bootstrapped U-statistics," Statistical Papers, Springer, vol. 61(4), pages 1685-1699, August.
  • Handle: RePEc:spr:stpapr:v:61:y:2020:i:4:d:10.1007_s00362-018-0999-8
    DOI: 10.1007/s00362-018-0999-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-018-0999-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00362-018-0999-8?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. Hall, Peter, 1990. "On the relative performance of bootstrap and Edgeworth approximations of a distribution function," Journal of Multivariate Analysis, Elsevier, vol. 35(1), pages 108-129, October.
    2. M. Vandemaele & N. Veraverbeke, 1985. "Cramer type large deviations for studentized U-statistics," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 32(1), pages 165-179, December.
    3. Borovskikh, Yuri V. & Robinson, John, 2008. "Large deviations of bootstrapped U -statistics," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1793-1806, September.
    4. Serfling, Robert & Wang, Wenyang, 2000. "A large deviation theorem for U-processes," Statistics & Probability Letters, Elsevier, vol. 49(2), pages 181-193, August.
    5. Dasgupta, Ratan, 2010. "Bootstrap of deviation probabilities with applications," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2137-2148, October.
    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. Inass Soukarieh & Salim Bouzebda, 2022. "Exchangeably Weighted Bootstraps of General Markov U -Process," Mathematics, MDPI, vol. 10(20), pages 1-42, 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. Andrea Pallini, 2000. "Efficient bootstrap estimation of distribution functions," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 81-95.
    2. Violetta Dalla & Javier Hidalgo, 2005. "A Parametric Bootstrap Test for Cycles," STICERD - Econometrics Paper Series 486, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Withers, Christopher S. & Nadarajah, Saralees, 2013. "Bayesian efficiency," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1203-1212.
    4. Borovskikh, Yuri V. & Robinson, John, 2008. "Large deviations of bootstrapped U -statistics," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1793-1806, September.
    5. Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 219-261.
    6. Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," LSE Research Online Documents on Economics 6829, London School of Economics and Political Science, LSE Library.
    7. Radulovic, Dragan, 2012. "A direct bootstrapping technique and its application to a novel goodness of fit test," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 181-199.
    8. Keener, Robert W. & Robinson, John & Weber, Neville C., 1998. "Tail probability approximations for U-statistics," Statistics & Probability Letters, Elsevier, vol. 37(1), pages 59-65, January.

    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:spr:stpapr:v:61:y:2020:i:4:d:10.1007_s00362-018-0999-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.