caa a22 4500 606196668 CHVBK 20210128100925.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s10260-015-0297-8 doi (NATIONALLICENCE)springer-10.1007/s10260-015-0297-8 Multivariate functional outlier detection [Elektronische Daten] [Mia Hubert, Peter Rousseeuw, Pieter Segaert] Functional data are occurring more and more often in practice, and various statistical techniques have been developed to analyze them. In this paper we consider multivariate functional data, where for each curve and each time point a $$p$$ p -dimensional vector of measurements is observed. For functional data the study of outlier detection has started only recently, and was mostly limited to univariate curves $$(p=1)$$ ( p = 1 ) . In this paper we set up a taxonomy of functional outliers, and construct new numerical and graphical techniques for the detection of outliers in multivariate functional data, with univariate curves included as a special case. Our tools include statistical depth functions and distance measures derived from them. The methods we study are affine invariant in $$p$$ p -dimensional space, and do not assume elliptical or any other symmetry. Springer-Verlag Berlin Heidelberg, 2015 Depth nationallicence Diagnostic plot nationallicence Functional data nationallicence Graphical display nationallicence Heatmap nationallicence Robustness nationallicence Hubert Mia Department of Mathematics, KU Leuven, Celestijnenlaan 200B, 3001, Heverlee, Belgium aut Rousseeuw Peter Department of Mathematics, KU Leuven, Celestijnenlaan 200B, 3001, Heverlee, Belgium aut Segaert Pieter Department of Mathematics, KU Leuven, Celestijnenlaan 200B, 3001, Heverlee, Belgium aut Statistical Methods & Applications Springer Berlin Heidelberg 24/2(2015-07-01), 177-202 1618-2510 24:2<177 2015 24 10260 https://doi.org/10.1007/s10260-015-0297-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10260-015-0297-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hubert Mia Department of Mathematics, KU Leuven, Celestijnenlaan 200B, 3001, Heverlee, Belgium aut NATIONALLICENCE 700 1- Rousseeuw Peter Department of Mathematics, KU Leuven, Celestijnenlaan 200B, 3001, Heverlee, Belgium aut NATIONALLICENCE 700 1- Segaert Pieter Department of Mathematics, KU Leuven, Celestijnenlaan 200B, 3001, Heverlee, Belgium aut NATIONALLICENCE 773 0- Statistical Methods & Applications Springer Berlin Heidelberg 24/2(2015-07-01), 177-202 1618-2510 24:2<177 2015 24 10260