Robust sliced inverse regression procedures

Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this relatively new method have been examined already, but little attention has been paid to robustness aspects. We show that SIR is very sensitive towards outliers in the data. Therefore a generalized estimation procedure which allows for robustness properties, especially for a high breakdown point, is proposed.

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Year of publication:	1998
Authors:	Gather, Ursula ; Hilker, Torsten ; Becker, Claudia
Publisher:	Dortmund : Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Subject:	Dimension reduction \| Outliers \| High breakdown procedures

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Series:	Technical Report ; 1998,22
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	816120390 [GVK] hdl:10419/77188 [Handle] RePEc:zbw:sfb475:199822 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010316531