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OWA operators in linear regression and detection of outliers

Beliakov, Gleb and Yager, Ronald R. 2009, OWA operators in linear regression and detection of outliers, in AGOP 2009 : Proceedings of the Fifth International Summer School on Aggregation Operators, Universitat de les Illes Balears, Palma, Spain, pp. 71-76.

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Title OWA operators in linear regression and detection of outliers
Author(s) Beliakov, Gleb
Yager, Ronald R.
Conference name International Summer School on Aggregation Operators (5th: 2009 : Parma, Spain)
Conference location Palma, Spain
Conference dates 6-10 July 2009
Title of proceedings AGOP 2009 : Proceedings of the Fifth International Summer School on Aggregation Operators
Editor(s) [Unknown]
Publication date 2009
Conference series Aggregation Operators Summer School
Start page 71
End page 76
Publisher Universitat de les Illes Balears
Place of publication Palma, Spain
Keyword(s) Aggregation operators
OWA
Robust Regresson
Least trimmed squares
Summary We consider the use of Ordered Weighted Averaging (OWA) in linear regression. Our goal is to replace the traditional least squares, least absolute deviation, and maximum likelihood criteria with an OWA function of the residuals. We obtain several high breakdown robust regression methods as special cases (least median, least trimmed squares, trimmed likelihood methods). We also present new formulations of regression problem. OWA-based regression is particularly useful in the presence of outliers.
ISBN 9788483841013
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2009, Edicions UIB
Persistent URL http://hdl.handle.net/10536/DRO/DU:30028312

Document type: Conference Paper
Collection: School of Information Technology
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