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Robust regression in Stata

delete2009-09-01
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V
Vincenzo Verardi *
C
Christophe Croux
DOI:10.1177/1536867X0900900306delete
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Abstract

Abstract

En 中文
In regression analysis, the presence of outliers in the dataset can strongly distort the classical least-squares estimator and lad to unreachable results To deal with this, several robust-to-outliers methods have been proposed in the statiscal literature. In Stata, some of these methods are available through the rreg and qreg commands. Unfortunately, these methods resist only some specific types of outhers and turn out to be ineffective under alternative scenarios. In this article, we present more effective robust estimators that we implemented in Stata We also present a graphical tool that recognizes the type of detected outtliers.
Keywords:
st0173
immregress
sregress
msregress
mcd
S-estimators
MM-estimators
outliers
robustness
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

S
Stata Journal
IF:
2.4
Papers:
1.2K
Citations:
8.4K

Organization

K
KU Leuven
Scholars:
5.7W
Papers: 5.2W
Citations: 8.1W
U
University of Namur
Scholars:
2.5K
Papers: 2.3K
Citations: 3.3K