Depth-based classification for functional data

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dc.contributor.author López Pintado, Sara
dc.contributor.author Romo, Juan
dc.date.accessioned 2006-11-09T10:58:07Z
dc.date.available 2006-11-09T10:58:07Z
dc.date.issued 2005-10
dc.identifier.uri http://hdl.handle.net/10016/231
dc.description.abstract Classification is an important task when data are curves. Recently, the notion of statistical depth has been extended to deal with functional observations. In this paper, we propose robust procedures based on the concept of depth to classify curves. These techniques are applied to a real data example. An extensive simulation study with contaminated models illustrates the good robustness properties of these depth-based classification methods.
dc.format.extent 597433 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 2005-11
dc.title Depth-based classification for functional data
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws055611
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