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Outlier Detection for Functional Data with R Package fdaoutlier
dc.contributor.author | Ojo, Oluwasegun | |
dc.contributor.author | Lillo, Rosa Elvira | |
dc.contributor.author | Fernández Anta, Antonio | |
dc.date.accessioned | 2021-07-13T09:49:55Z | |
dc.date.available | 2021-07-13T09:49:55Z | |
dc.date.issued | 2021-05 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12761/980 | |
dc.description.abstract | Outlier 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.iso | eng | |
dc.publisher | arXiv | |
dc.title | Outlier Detection for Functional Data with R Package fdaoutlier | en |
dc.type | technical report | |
dc.rights.accessRights | open access | |
dc.identifier.doi | arXiv:2105.05213 [stat.CO] | |
dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/2336 |