Search

Searching. Please wait…

Detalle_Publicacion

A topologically valid construction of depth for functional data

Abstract: Numerous problems remain in the construction of statistical depth for functional data. Issues stem largely from the absence of a well-conceived notion of symmetry. The present paper proposes a topologically valid notion of symmetry for distributions on functional metric spaces and a corresponding notion of depth. The latter is shown to satisfy the axiomatic definition of functional depth introduced by Nieto-Reyes and Battey (2016).

 Fuente: Journal of Multivariate Analysis, 2021, 184

Publisher: Academic Press Inc.

 Publication date: 01/07/2021

No. of pages: 16

Publication type: Article

 DOI: 10.1016/j.jmva.2021.104738

ISSN: 0047-259X,1095-7243

 Spanish project: MTM2017-86061-C2-2-P (to AN-R)

Publication Url: https://doi.org/10.1016/j.jmva.2021.104738

Authorship

BATTEY, HEATHER