IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v126y2017icp179-184.html
   My bibliography  Save this article

Error bounds for kernel density estimator of spectral distribution for Gaussian Unitary Ensembles

Author

Listed:
  • Jiang, Hui
  • Wang, Shaochen

Abstract

In this short note, we study the error bounds for kernel density estimator of spectral distribution for Gaussian unitary ensembles. A deviation inequality and L1 error bound for the kernel estimator have been obtained. Our approach is based on an abstract deviation inequality for linear spectrum statistics of determinantal points fields.

Suggested Citation

  • Jiang, Hui & Wang, Shaochen, 2017. "Error bounds for kernel density estimator of spectral distribution for Gaussian Unitary Ensembles," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 179-184.
  • Handle: RePEc:eee:stapro:v:126:y:2017:i:c:p:179-184
    DOI: 10.1016/j.spl.2017.03.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715217301141
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spl.2017.03.014?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

    Keywords

    Kernel density estimator; Gaussian unitary ensembles; Deviation inequality; L1 error bound;
    All these keywords.

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    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:eee:stapro:v:126:y:2017:i:c:p:179-184. 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.