IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v5y1987i3p219-224.html
   My bibliography  Save this article

Nonparametric orthogonal series estimators of regression: A class attaining the optimal convergence rate in L2

Author

Listed:
  • Rafaj[left ceiling]owicz, Ewaryst

Abstract

In this note a class of nonparametric orthogonal series type estimators for regression function fitting is considered. Sufficient conditions are given for the estimators to attain the optimal convergence rate in the mean integrated square error sense. Using results from the theory of numerical integration, examples of estimators are given, for which the above mentioned conditions hold.

Suggested Citation

  • Rafaj[left ceiling]owicz, Ewaryst, 1987. "Nonparametric orthogonal series estimators of regression: A class attaining the optimal convergence rate in L2," Statistics & Probability Letters, Elsevier, vol. 5(3), pages 219-224, April.
    • Handle: RePEc:eee:stapro:v:5:y:1987:i:3:p:219-224
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(87)90044-7
    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.

    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:5:y:1987:i:3:p:219-224. 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.