High order data sharpening for density estimation
Peter Hall and
Michael C. Minnotte
Journal of the Royal Statistical Society Series B, 2002, vol. 64, issue 1, 141-157
Abstract:
It is shown that data sharpening can be used to produce density estimators that enjoy arbitrarily high orders of bias reduction. Practical advantages of this approach, relative to competing methods, are demonstrated. They include the sheer simplicity of the estimators, which makes code for computing them particularly easy to write, very good mean‐squared error performance, reduced `wiggliness' of estimates and greater robustness against undersmoothing.
Date: 2002
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
https://doi.org/10.1111/1467-9868.00329
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssb:v:64:y:2002:i:1:p:141-157
Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9868
Access Statistics for this article
Journal of the Royal Statistical Society Series B is currently edited by P. Fryzlewicz and I. Van Keilegom
More articles in Journal of the Royal Statistical Society Series B from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().