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Resumen de Generalized additive models for functional data

Manuel Febrero Bande Árbol académico, Wenceslao González Manteiga Árbol académico

  • The aim of this paper is to extend the ideas of generalized additive models for multivariate data (with known or unknown link function) to functional data covariates. The proposed algorithm is a modified version of the local scoring and backfitting algorithms that allows for the nonparametric estimation of the link function. This algorithm would be applied to predict a binary response example


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