Extremal Depth for Functional Data and Applications

We propose a new notion called "extremal depth" (ED) for functional data, discuss its properties, and compare its performance with existing concepts. The proposed notion is based on a measure of extreme "outlyingness." ED has several desirable properties that are not shared by ot...

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Veröffentlicht in:	Journal of the American Statistical Association Jg. 111; H. 516; S. 1705 - 1714
Hauptverfasser:	Narisetty, Naveen N., Nair, Vijayan N.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Alexandria Taylor & Francis 01.12.2016 Taylor & Francis Group,LLC Taylor & Francis Ltd
Schlagworte:	Central regions Data Data depth equations Functional boxplots Outlier detection probability Property Regions Regression analysis Simultaneous inference Statistics Theory and Methods Usefulness
ISSN:	0162-1459, 1537-274X, 1537-274X
Online-Zugang:	Volltext
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