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Hall, P. and Jones, Chris
(1990).
Abstract
A method for robust nonparametric regression is discussed. A method for robust nonparametric regression is discussed. We consider kernel M-estimates of the regression function using Huber's ψ-function and extend results of Hardle and Gasser to the case of random designs. A practical adaptive procedure is proposed consisting of simultaneously minimising a cross-validatory criterion with respect to both the smoothing parameter and a robustness parameter occurring in the ψ-function. This method is shown to possess a theoretical asymptotic optimality property, while some simulated examples confirm that the approach is practicable.
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About
- Item ORO ID
- 28321
- Item Type
- Journal Item
- ISSN
- 0090-5364
- Keywords
- cross-validation; Huber's ψ function; kernel estimation; robust smoothing
- 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
- © 1990 Institute of Mathematical Statistics
- Depositing User
- Sarah Frain