RT Generic
T1 Kernel depth funcions for functional data
A1 Hernández Banadik, Nicolás Jorge
A1 Muñoz García, Alberto
A2 Universidad Carlos III de Madrid. Departamento de Estadística, 
AB In the last years the concept of data depth has been increasingly used in Statistics as a center-outward ordering of sample points in multivariate data sets. Recently data depth has been extended to functional data. In this paper we propose new intrinsic functional data depths based on the representation of functional data on Reproducing Kernel Hilbert Spaces, and test its performance against a number of well known alternatives in the problem of functional outlier detection.
SN 2387-0303
YR 2017
FD 2017-04
LK https://hdl.handle.net/10016/24615
UL https://hdl.handle.net/10016/24615
LA eng
NO The authors acknowledge financial support from the Spanish Ministry of Economy and Competitiveness ECO2015-66593-P.
DS e-Archivo
RD 23 may. 2024