Robust regression based on shrinkage with application to Living Environment Deprivation

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dc.citation.journalTitleSTOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENTeng
dc.contributor.authorCabana E.
dc.contributor.authorLillo R.E.
dc.contributor.authorLaniado H.
dc.contributor.departmentUniversidad EAFIT. Escuela de Cienciasspa
dc.contributor.researchgroupModelado Matemáticospa
dc.date.accessioned2021-04-12T14:07:18Z
dc.date.available2021-04-12T14:07:18Z
dc.date.issued2020-01-01
dc.description.abstractA robust estimator is proposed for the parameters that characterize the linear regression problem. It is based on the notion of shrinkages, often used in Finance and previously studied for outlier detection in multivariate data. A thorough simulation study is conducted to investigate: the efficiency with Normal and heavy-tailed errors, the robustness under contamination, the computational time, the affine equivariance and breakdown value of the regression estimator. Two classical data-sets often used in the literature and a real socioeconomic data-set about the Living Environment Deprivation of areas in Liverpool (UK), are studied. The results from the simulations and the real data examples show the advantages of the proposed robust estimator in regression. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=10276
dc.identifier.doi10.1007/s00477-020-01774-4
dc.identifier.issn14363240
dc.identifier.issn14363259
dc.identifier.otherWOS;000511081000001
dc.identifier.otherSCOPUS;2-s2.0-85079182594
dc.identifier.urihttp://hdl.handle.net/10784/27819
dc.language.isoengeng
dc.publisherSpringer
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85079182594&doi=10.1007%2fs00477-020-01774-4&partnerID=40&md5=136d0772c3ab858e826c125460d8ff81
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1436-3240
dc.sourceSTOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
dc.subject.keywordRegression analysiseng
dc.subject.keywordStatisticseng
dc.subject.keywordEnvironmental studieseng
dc.subject.keywordMahalanobis distanceseng
dc.subject.keywordOutlierseng
dc.subject.keywordRobust regressionseng
dc.subject.keywordShrinkage estimatoreng
dc.subject.keywordShrinkageeng
dc.titleRobust regression based on shrinkage with application to Living Environment Deprivationeng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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