A robust partial least squares method with applications

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dc.contributor.author González, Javier
dc.contributor.author Peña, Daniel
dc.contributor.author Romera, Rosario
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2007-03-22T13:53:18Z
dc.date.available 2007-03-22T13:53:18Z
dc.date.issued 2007-03
dc.identifier.uri http://hdl.handle.net/10016/665
dc.description.abstract Partial least squares regression (PLS) is a linear regression technique developed to relate many regressors to one or several response variables. Robust methods are introduced to reduce or remove the effect of outlying data points. In this paper we show that if the sample covariance matrix is properly robustified further robustification of the linear regression steps of the PLS algorithm becomes unnecessary. The robust estimate of the covariance matrix is computed by searching for outliers in univariate projections of the data on a combination of random directions (Stahel-Donoho) and specific directions obtained by maximizing and minimizing the kurtosis coefficient of the projected data, as proposed by Peña and Prieto (2006). It is shown that this procedure is fast to apply and provides better results than other procedures proposed in the literature. Its performance is illustrated by Monte Carlo and by an example, where the algorithm is able to show features of the data which were undetected by previous methods.
dc.format.extent 245726 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 07-04
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Kurtosis
dc.subject.other Projections
dc.subject.other Robust covariance matrix
dc.subject.other Stahel-Donoho estimator
dc.title A robust partial least squares method with applications
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws071304
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