@techreport{Tamine2001Smoothed,
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.},
address = {Berlin},
author = {Julien Tamine},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C13; C14; C15; 330; robustness; nonparametric regression; influence function; M-estimator; L-estimator; R-estimator; Von-mises statistical functional generalized Delta-theorem},
language = {eng},
note = {urn:nbn:de:kobv:11-10049243},
number = {2002,62},
publisher = {Humboldt-Universit\"{a}t},
title = {Smoothed influence function: Another view at robust nonparametric regression},
type = {Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes},
url = {http://hdl.handle.net/10419/65369},
year = {2001}
}
