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dc.contributor.authorOjo, Oluwasegun 
dc.contributor.authorLillo, Rosa Elvira
dc.contributor.authorFernández Anta, Antonio 
dc.date.accessioned2021-07-13T09:49:55Z
dc.date.available2021-07-13T09:49:55Z
dc.date.issued2021-05
dc.identifier.urihttp://hdl.handle.net/20.500.12761/980
dc.description.abstractOutlier detection is one of the standard exploratory analysis tasks in functional data analysis. We present the R package fdaoutlier which contains implementations of some of the latest techniques for detecting functional outliers. The package makes it easy to detect different types of outliers (magnitude, shape, and amplitude) in functional data, and some of the implemented methods can be applied to both univariate and multivariate functional data. We illustrate the main functionality of the R package with common functional datasets in the literature.
dc.language.isoeng
dc.publisherarXiv
dc.titleOutlier Detection for Functional Data with R Package fdaoutlieren
dc.typetechnical report
dc.rights.accessRightsopen access
dc.identifier.doiarXiv:2105.05213 [stat.CO]
dc.eprint.idhttp://eprints.networks.imdea.org/id/eprint/2336


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