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, Volume 22, Issue 2, pp 278–292 | Cite as

Generalized additive models for functional data

  • Manuel Febrero-BandeEmail author
  • Wenceslao González-Manteiga
Original Paper

Abstract

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.

Keywords

Functional data Generalized additive models Generalized linear models 

Mathematics Subject Classification

62G08 62J12 

Notes

Acknowledgements

The authors are grateful to the editor and three anonymous referees for their useful comments. This research has been partially funded by project MTM2008-03010 from Ministerio de Ciencia e Innovación, Spain and by project 10MDS207015PR from Xunta de Galicia, Spain.

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Copyright information

© Sociedad de Estadística e Investigación Operativa 2012

Authors and Affiliations

  • Manuel Febrero-Bande
    • 1
    Email author
  • Wenceslao González-Manteiga
    • 1
  1. 1.Dpt. of Statistics and O.R. Faculty of MathematicsUniversity of Santiago de CompostelaSantiago de CompostelaSpain

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