Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/65369
Authors: 
Tamine, Julien
Year of Publication: 
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: 
Document Type: 
Working Paper

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