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dc.contributor.advisorLaniado Rojas,Henry; 98625503spa
dc.coverage.spatialMedellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degreeseng
dc.creatorVelasco Vera, Henry Giovanny
dc.date.available2019-02-14T19:28:23Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/10784/13405
dc.description.abstractCellwise and casewise outliers may appear both at the same time in real data. Few methods have developed statistical methods to deal both types of outliers in regression models. We propose a new three-step regression method that uses the comedian as highly robust scatter estimate in a known threestep regression (3S-regression). The procedure introduced here, shows in general, an outperformance respect to recent robust methods. We test the comedian three-step regression (C3S-regression) in both synthetic and real data. The results of this paper show that the proposed C3S-regression is highly robust in presence of cellwise and casewise outliers. We also extend the results to models with continuous and dummy covariates.spa
dc.language.isospaspa
dc.rightsinfo:eu-repo/semantics/closedAccessspa
dc.subjectregresiónspa
dc.titleRobust three-step regression based on comedian and its performance in cellwise and casewise outliersspa
dc.typemasterThesiseng
dc.typeinfo:eu-repo/semantics/masterThesiseng
dc.rights.accessRightsclosedAccessspa
dc.publisher.programMaestría en Matemáticas Aplicadasspa
dc.subject.lembAnálisis de regresión-modelos matemáticosspa
dc.publisher.departmentEscuela de Ciencias. Departamento de Ciencias Básicasspa
dc.creator.degreeMagíster en Matemáticas Aplicadasspa
dc.type.spaTesis de Maestríaspa
dc.subject.keywordCellwise outlierspa
dc.subject.keywordCasewise contaminationspa
dc.subject.keywordComedianspa
dc.subject.keywordGeneralized Rocke S-Estimatorspa
dc.subject.keyword3S-regressionspa
dc.rights.accesoAcceso cerradospa
dc.date.accessioned2019-02-14T19:28:23Z
dc.type.hasVersionacceptedVersioneng
dc.creator.emailhgvelascov@eafit.edu.cospa
dc.identifier.ddc519.5 V433


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