, Volume 26, Issue 1, pp 119–142 | Cite as

The \(\hbox {DD}^G\)-classifier in the functional setting

  • J. A. Cuesta-Albertos
  • M. Febrero-Bande
  • M. Oviedo de la FuenteEmail author
Original Paper


The maximum depth classifier was the first attempt to use data depths instead of multivariate raw data in classification problems. Recently, the DD-classifier has addressed some of the serious limitations of this classifier but issues still remain. This paper aims to extend the DD-classifier as follows: first, by enabling it to handle more than two groups; second, by applying regular classification methods (such as kNN, linear or quadratic classifiers, recursive partitioning, etc) to DD-plots, which is particularly useful, because it gives insights based on the diagnostics of these methods; and third, by integrating various sources of information (data depths, multivariate functional data, etc) in the classification procedure in a unified way. This paper also proposes an enhanced revision of several functional data depths and it provides a simulation study and applications to some real data sets.


DD-classifier Functional depths Functional data analysis 

Mathematics Subject Classification

62-09 62G99 62H30 



This research was partially supported by the Spanish Ministerio de Ciencia y Tecnología, Grants MTM2011-28657-C02-02, MTM2014-56235-C2-2-P (J.A. Cuesta–Albertos) and MTM2013-41383-P (M. Febrero–Bande and M. Oviedo de la Fuente).

Supplementary material

11749_2016_502_MOESM1_ESM.rar (4.1 mb)
Supplementary material 1 (rar 4166 KB)


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Copyright information

© Sociedad de Estadística e Investigación Operativa 2016

Authors and Affiliations

  1. 1.Department of Mathematics, Statistics and ComputationUniversity of CantabriaSantanderSpain
  2. 2.Department of Statistics and Operations ResearchUniversity of Santiago de CompostelaSantiago de CompostelaSpain

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