Title: The shooting S-estimator for robust regression
Authors: Oellerer, Viktoria
Alfons, Andreas
Croux, Christophe
Issue Date: Nov-2013
Publisher: KU Leuven - Faculty of Economics and Business
Series Title: FEB Research Report KBI_1318
Abstract: To perform multiple regression, the least squares estimator is commonly used. However, this estimator is not robust to outliers. Therefore, robust methods such as MM-estimation have been proposed. These estimators flag any observation with a large residual as an outlier and downweight it in the further procedure. This is also the case if the large residual is caused by only one component of the observation, which results in a loss of information. Therefore, we propose the shooting S-estimator, a regression estimator that is especially designed for situations where a large number of observations suffer from contamination in a small number of predictor variables. The shooting S-estimator combines the ideas of the coordinate descent algorithm with simple S-regression, which makes it robust against componentwise contamination.
Publication status: published
KU Leuven publication type: IR
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven

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