IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v47y2018i16p3871-3892.html
   My bibliography  Save this article

On the mean L1-error in the heteroscedastic deconvolution problem with compactly supported noises

Author

Listed:
  • Cao Xuan Phuong
  • Dang Duc Trong
  • Tran Quoc Viet

Abstract

We study the heteroscedastic deconvolution problem when random noises have compactly supported densities. In this context, the Fourier transforms of the densities can vanish on the real line. We propose a truncated type of estimator for target density and derive the convergence rate of the mean L1-error uniformly over a class of target densities. A lower bound for the mean L1-error is also established. Some simulations will be given to illustrate the performance of the proposed estimator.

Suggested Citation

  • Cao Xuan Phuong & Dang Duc Trong & Tran Quoc Viet, 2018. "On the mean L1-error in the heteroscedastic deconvolution problem with compactly supported noises," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(16), pages 3871-3892, August.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:16:p:3871-3892
    DOI: 10.1080/03610926.2017.1364389
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2017.1364389
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2017.1364389?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.

    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:taf:lstaxx:v:47:y:2018:i:16:p:3871-3892. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.