Depth-based inference for functional data

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dc.contributor.author López Pintado, Sara
dc.contributor.author Romo, Juan
dc.date.accessioned 2006-11-09T10:59:41Z
dc.date.available 2006-11-09T10:59:41Z
dc.date.issued 2006-05
dc.identifier.uri http://hdl.handle.net/10016/244
dc.description.abstract We propose robust inference tools for functional data based on the notion of depth for curves. We extend the ideas of trimmed regions, contours and central regions to functions and study their structural properties and asymptotic behavior. Next, we introduce a scale curve to describe dispersion in a sample of functions. The computational burden of these techniques is not heavy and so they are also adequate to analyze high-dimensional data. All these inferential methods are applied to different real data sets.
dc.format.extent 557852 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 2006-13
dc.title Depth-based inference for functional data
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws063113
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