IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v207y2024ics0167715223002389.html
   My bibliography  Save this article

Efficiency of the averaged rank-based estimator for first order Sobol index inference

Author

Listed:
  • Klein, Thierry
  • Rochet, Paul

Abstract

Among the many estimators of first order Sobol indices that have been proposed in the literature, the so-called rank-based estimator is arguably the simplest to implement. This estimator can be viewed as the empirical auto-correlation of the response variable sample obtained upon re-ordering the data by increasing values of the inputs. This simple idea can be extended to higher lags of auto-correlation, thus providing several competing estimators of the same parameter. We show that these estimators can be combined in a simple manner to achieve the theoretical variance efficiency bound asymptotically

Suggested Citation

  • Klein, Thierry & Rochet, Paul, 2024. "Efficiency of the averaged rank-based estimator for first order Sobol index inference," Statistics & Probability Letters, Elsevier, vol. 207(C).
  • Handle: RePEc:eee:stapro:v:207:y:2024:i:c:s0167715223002389
    DOI: 10.1016/j.spl.2023.110015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715223002389
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spl.2023.110015?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.

    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:207:y:2024:i:c:s0167715223002389. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.