Kernel-based functional principal components

In this paper, we propose kernel-based smooth estimates of the functional principal components when data are continuous trajectories of stochastic processes. Strong consistency and the asymptotic distribution are derived under mild conditions. © 2000 Elsevier Science B.V.

Guardado en:
Detalles Bibliográficos
Autores principales: Boente, G., Fraiman, R.
Formato: JOUR
Lenguaje:English
Materias:
62H25
Eigenfunctions
Functional principal components
Kernel methods* Hilbert-Schmidt operators
Primary 62G07
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01677152_v48_n4_p335_Boente
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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