Shrinkage reweighted regression

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Show simple item record Cabana Garceran del Vall, Elisa Lillo Rodríguez, Rosa Elvira Laniado Rodas, Henry
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2019-06-14T13:18:13Z 2019-06-14T13:18:13Z 2019-06
dc.identifier.issn 2387-0303
dc.description.abstract A 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 times, the affine equivariance and breakdown value of the regression estimator. Two classical data-sets often used in the literature and a real socio-economic 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.
dc.description.sponsorship This research was partially supported by MINISTERIO DE ECONOMIA, INDUSTRIA Y COMPETITIVIDAD, award number: ECO2015-66593-P.
dc.language.iso eng
dc.relation.ispartofseries Working paper. Statistics and Econometrics
dc.relation.ispartofseries 19-08
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Robust Regression
dc.subject.other Robust Mahalanobis Distance
dc.subject.other Shrinkage Estimator
dc.subject.other Outliers
dc.subject.other Environmental Study
dc.title Shrinkage reweighted regression
dc.type workingPaper
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. ECO2015-66593-P
dc.type.version draft
dc.identifier.uxxi DT/0000001713
dc.contributor.funder Ministerio de Economía y Competitividad (España)
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