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Title:Smoothed influence function: Another view at robust nonparametric regression PDF Logo
Authors:Tamine, Julien
Issue Date:2001
Series/Report no.:Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 2002,62
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.
Subjects:robustness
nonparametric regression
influence function
M-estimator
L-estimator
R-estimator
Von-mises statistical functional generalized Delta-theorem
JEL:C13
C14
C15
Persistent Identifier of the first edition:urn:nbn:de:kobv:11-10049243
Document Type:Working Paper
Appears in Collections:Discussion Papers, SFB 373, HU Berlin

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