We introduce a generalization of the simplicial depth measure to multivariate functional data, exploiting the role of the variance-covariance operators in weighting the components that define the depth. We propose the use of this nonparametric method for supervised classification purpose.
Multivariate functional data depth measure based on variance-covariance operators / R. Biasi, F. Ieva, A.M. Paganoni, N. Tarabelloni - In: Contributions in infinite dimensional statistics and related topics / [a cura di] E. Bongiorno, A. Goia, E. Salinelli, P. Vieu. - [s.l] : ESCULAPIO, 2014 Jun 18. - ISBN 978-88-7488-763-7. - pp. 49-54 (( Intervento presentato al 3. convegno International Workshop on Functional and Operatorial Statistics tenutosi a Stresa nel 2014.
Multivariate functional data depth measure based on variance-covariance operators
F. IevaSecondo
;
2014
Abstract
We introduce a generalization of the simplicial depth measure to multivariate functional data, exploiting the role of the variance-covariance operators in weighting the components that define the depth. We propose the use of this nonparametric method for supervised classification purpose.
| File | Dimensione | Formato | |
|---|---|---|---|
|
Biasi_et_al_iwfos14_final.pdf
accesso aperto
Tipologia:
Publisher's version/PDF
Dimensione
213.38 kB
Formato
Adobe PDF
|
213.38 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
