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OWA operators in regression problems

Yager, Ronald R. and Beliakov, Gleb 2010, OWA operators in regression problems, IEEE transactions on fuzzy systems, vol. 18, no. 1, pp. 106-113.

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Title OWA operators in regression problems
Author(s) Yager, Ronald R.
Beliakov, Gleb
Journal name IEEE transactions on fuzzy systems
Volume number 18
Issue number 1
Start page 106
End page 113
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2010-02
ISSN 1063-6706
1941-0034
Keyword(s) aggregation operators
least trimmed squares (LTS)
outliers
ordered weighted averaging (OWA)
robust regression
Summary We consider an application of fuzzy logic connectives to statistical regression. We replace the standard least squares, least absolute deviation, and maximum likelihood criteria with an ordered weighted averaging (OWA) function of the residuals. Depending on the choice of the weights, we obtain the standard regression problems, high-breakdown robust methods (least median, least trimmed squares, and trimmed likelihood methods), as well as new formulations. We present various approaches to numerical solution of such regression problems. OWA-based regression is particularly useful in the presence of outliers, and we illustrate the performance of the new methods on several instances of linear regression problems with multiple outliers.
Notes 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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 C1 Refereed article in a scholarly journal
HERDC collection year 2010
Copyright notice ©2009, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30028316

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.