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dc.contributor.authorPınar, M. Ç.en_US
dc.date.accessioned2016-02-08T10:31:18Z
dc.date.available2016-02-08T10:31:18Z
dc.date.issued2002en_US
dc.identifier.issn0006-3835
dc.identifier.urihttp://hdl.handle.net/11693/24573
dc.description.abstractThe purpose of this note is to present a robust counterpart of the Huber estimation problem in the sense of Ben-Tal and Nemirovski when the data elements are subject to ellipsoidal uncertainty. The robust counterparts are polynomially solvable second-order cone programs with the strong duality property. We illustrate the effectiveness of the robust counterpart approach on a numerical example.en_US
dc.language.isoEnglishen_US
dc.source.titleBIT Numerical Mathematicsen_US
dc.relation.isversionofhttps://link.springer.com/article/10.1023%2FA%3A1021960722440en_US
dc.subjectData fittingen_US
dc.subjectHuber's M-estimatoren_US
dc.subjectLeast squares problemsen_US
dc.subjectRobustnessen_US
dc.subjectSecond-order cone programmingen_US
dc.titleLinear huber M-estimator under ellipsoidal data uncertaintyen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage856en_US
dc.citation.epage866en_US
dc.citation.volumeNumber42en_US
dc.citation.issueNumber4en_US
dc.identifier.doi10.1023/A:1021960722440en_US
dc.publisherSpringeren_US


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