Jones, M. C.
(2000).
| DOI (Digital Object Identifier) Link: | https://doi.org/10.1111/1467-9574.00124 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
In nonparametric estimation of functionals of a distribution, it may or may not be desirable, or indeed necessary, to introduce a degree of smoothing into this estimation. In this article, I describe a method for assessing, with just a little thought about the functional of interest, (i) whether smoothing is likely to prove worthwhile, and (ii) if so, roughly how much smoothing is appropriate (in order-of-magnitude terms). This rule-of-thumb is not guaranteed to be accurate nor does it give a complete answer to the smoothing problem. However, I have found it very useful over a number of years; many examples of its use, and limitations, are given.
| Item Type: | Article |
|---|---|
| Copyright Holders: | 2000 VVS |
| ISSN: | 1467-9574 |
| Keywords: | bandwidth;density derivatives;empirical distribution function;kernel density estimation;kernel functional estimation;mean squared error;smoothed bootstrapping |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Item ID: | 23863 |
| Depositing User: | Sarah Frain |
| Date Deposited: | 05 Apr 2011 13:59 |
| Last Modified: | 04 Oct 2016 10:46 |
| URI: | http://oro.open.ac.uk/id/eprint/23863 |
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