Title: Robust regression in Stata
Authors: Verardi, Vincenzo
Croux, Christophe
Issue Date: Nov-2008
Publisher: K.U.Leuven
Series Title: FBE Research Report KBI_0823 pages:1-13
Abstract: In regression analysis, the presence of outliers in the data set can strongly distort the classical least squares estimator and lead to unreliable results. To deal with this, several robust-to-outliers methods have been proposed in the statistical literature. In Stata, some of these methods are available through the commands rreg and qreg. Unfortunately, these methods only resist to some specific types of outliers and turn out to be ineffective under alternative scenarios. In this paper we present more effective robust estimators that we implemented in Stata. We also present a graphical tool that allows recognizing the type of existing outliers.
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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