IDEAS home Printed from https://ideas.repec.org/p/wop/agsmst/95008.html
   My bibliography  Save this paper

Accuracy of Binned Kernel Functional Approximations

Author

Listed:
  • Gonzalez-Manteiga, W.
  • Sanchez-Sellero, C.
  • Wand, M.P.

Abstract

Virtually all common bandwidth selection algorithms are based on a certain type of kernel functional estimator. Such estimators can be very computationally expensive, so in practice they are often replaced by fast binned approximations. This is especially worthwhile when the bandwidth selection method involves iteration. Results for the accuracy of these approximations are derived and then used to provide an understanding of the number of binning grid points required to achieve a given level of accuracy Our results apply to both univariate and multivariate settings. Multivariate contexts are of particular interest since the cost due to having a higher number of grid points can be quite significant.

Suggested Citation

  • Gonzalez-Manteiga, W. & Sanchez-Sellero, C. & Wand, M.P., "undated". "Accuracy of Binned Kernel Functional Approximations," Statistics Working Paper 95008, Australian Graduate School of Management.
  • Handle: RePEc:wop:agsmst:95008
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:wop:agsmst:95008. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/gsnswau.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.