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Kernel-based functional principal components

Graciela Boente and Ricardo Fraiman

Statistics & Probability Letters, 2000, vol. 48, issue 4, 335-345

Abstract: 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.

Keywords: Functional; principal; components; Kernel; methods; Hilbert-Schmidt; operators; Eigenfunctions (search for similar items in EconPapers)
Date: 2000
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