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Jones, M. C.
(2000).
DOI: https://doi.org/10.1111/1467-9574.00124
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.
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About
- Item ORO ID
- 23863
- Item Type
- Journal Item
- ISSN
- 1467-9574
- Keywords
- bandwidth;density derivatives;empirical distribution function;kernel density estimation;kernel functional estimation;mean squared error;smoothed bootstrapping
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2000 VVS
- Depositing User
- Sarah Frain