Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/5728

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dc.contributor.authorFaria, Susana-
dc.contributor.authorMelfi, Giuseppe-
dc.date.accessioned2006-10-26T15:14:56Z-
dc.date.available2006-10-26T15:14:56Z-
dc.date.issued2006-07-
dc.identifier.citationINTERNATIONAL CONFERENCE ON ROBUST STATISTICS, Lisboa, 2006 – “ICORS06 - International Conference on Robust Statistics”. ". [S.l. : s.n., 2006].eng
dc.identifier.urihttps://hdl.handle.net/1822/5728-
dc.description.abstractThe detection of outliers for the standard least squares regression is a problem which has been extensevily studied. Lad Regression diagnostics offers alternative approaches whose main feature is the robustness. In this work, we propose a nonparametric method for detecting outliers in LAD regression models and compare t to other classical methods.eng
dc.description.sponsorshipThe European Science Foundation, The Minerva Research Foundation, CEMAT, UIMA, INE,SPSS, Timberlake Consultantseng
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectLad regressioneng
dc.subjectRobustnesseng
dc.subjectOutlierseng
dc.titleA non parametric robust method for the detection of outliers in linear modelseng
dc.typeconferenceAbstracteng
dc.peerreviewedyeseng
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