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Bandwidth selection in robust smoothing
Authors:
Denis H. Y. Leungi a;
Francis H. C. Marriott b;
Eden K. H. Wu a
| Affiliations: | a The Chinese University of Hong Kong, |
| b University of Oxford, |
DOI:
10.1080/10485259308832562
Publication Frequency:
8 issues per year
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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(English)
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Abstract
In robust smoothing of regression functions of the type
 , the theory in automatic bandwidth selection is still lacking. This paper tries to fill the gap by looking at the use of cross-validation methods in robust smoothing. Conjectures regarding the use of a class of robust cross-validation method are made. These are further complemented by examples, all of which showed favourably for the new method.
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| Keywords: Nonparametric regression; smoothing; kernel; bandwidth; robust smoothers; cross-validation; m-estimation |
| view references (18) |
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