Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/38622
Type: Artigo de periódico
Title: Adaptive basis selection for functional data analysis via stochastic penalization
Author: Anselmo, Cezar A.F.
Dias, Ronaldo
Garcia, Nancy L.
Abstract: We propose an adaptive method of analyzing a collection of curves which can be, individually, modeled as a linear combination of spline basis functions. Through the introduction of latent Bernoulli variables, the number of basis functions, the variance of the error measurements and the coefficients of the expansion are determined. We provide a modification of the stochastic EM algorithm for which numerical results show that the estimates are very close to the true curve in the sense of L2 norm.
Subject: basis functions
SEM algorithm
functional statistics
summary measures
splines
non-parametric data analysis
registration
Editor: Sociedade Brasileira de Matemática Aplicada e Computacional
Rights: aberto
Identifier DOI: 10.1590/S0101-82052005000200004
Address: http://dx.doi.org/10.1590/S0101-82052005000200004
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022005000200004
Date Issue: 1-Aug-2005
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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