Smoothed influence function: Another view at robust nonparametric regression

Julien Tamine

No 2002,62, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show that the M, the L and the R-estimators of the regression achieve robustness (when estimated by kernel). Our results are illustrated performing Monte-Carlo simulation.

Keywords: robustness; nonparametric regression; influence function; M-estimator; L-estimator; R-estimator; Von-mises statistical functional generalized Delta-theorem (search for similar items in EconPapers)
JEL-codes: C13 C14 C15 (search for similar items in EconPapers)
Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:200262

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