Shape outlier detection and visualization for functional data: the outliergram

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dc.contributor.author Arribas Gil, Ana
dc.contributor.author Romo, Juan
dc.date.accessioned 2021-07-15T10:42:32Z
dc.date.available 2021-07-15T10:42:32Z
dc.date.issued 2014-10-01
dc.identifier.bibliographicCitation Arribas-Gil, A., & Romo, J. (2014). Shape outlier detection and visualization for functional data: the outliergram. Biostatistics, 15(4), 603–619
dc.identifier.issn 1465-4644
dc.identifier.uri http://hdl.handle.net/10016/33087
dc.description.abstract We propose a new method to visualize and detect shape outliers in samples of curves. In functional data analysis we observe curves defined over a given real interval and shape outliers may be defined as those curves that exhibit a different shape from the rest of the sample. Whereas magnitude outliers, that is, curves that lie outside the range of the majority of the data, are in general easy to identify, shape outliers are often masked among the rest of the curves and thus difficult to detect. In this article we exploit the relation between two measures of depth for functional data to help visualizing curves in terms of shape and to develop an algorithm for shape outlier detection. We illustrate the use of the visualization tool, the outliergram, through several examples and assess the performance of the algorithm on a simulation study. Finally, we apply our method to identify outliers in real data sets of growth and mortality curves.
dc.language.iso eng
dc.publisher Oxford University Press
dc.rights ©The Author 2013. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
dc.subject.other Depth for functional data
dc.subject.other Outlier visualization
dc.subject.other Robust estimation
dc.subject.other Time course microarray data
dc.subject.other Boxplots
dc.subject.other Depth
dc.title Shape outlier detection and visualization for functional data: the outliergram
dc.type article
dc.subject.eciencia Estadística
dc.identifier.doi https://doi.org/10.1093/biostatistics/kxu006
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 603
dc.identifier.publicationissue 4
dc.identifier.publicationlastpage 619
dc.identifier.publicationtitle Biostatistics
dc.identifier.publicationvolume 15
dc.identifier.uxxi AR/0000015775
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