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.
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Autores principales: | , |
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Formato: | JOUR |
Lenguaje: | English |
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Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_01677152_v48_n4_p335_Boente |
Aporte de: |
Sumario: | 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. |
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