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Thresholding in Nonparametric Functional Regression with Scalar Response

  • Frédéric Ferraty
  • Adela Martínez-Calvo
  • Philippe Vieu
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

In this work, we have focused on the nonparametric regression model with scalar response and functional covariate, and we have analyzed the existence of underlying complex structures in data by means of a thresholding procedure. Several thresholding functions are proposed, and a cross-validation criterion is used in order to estimate the threshold value. Furthermore, a simulation study shows the effectiveness of our method.

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References

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    Ait-Saïdi, A., Ferraty, F., Kassa, R., Vieu, P.: Cross-validated estimations in the singlefunctional index model. Statistics 42 (6), 475–494 (2008)Google Scholar
  2. 2.
    Ferraty, F., Mas, A., Vieu, P.: Nonparametric regression on functional data: inference and practical aspects. Aust. N.Z. J. Stat. 49 (3), 267–286 (2007)Google Scholar
  3. 3.
    Ferraty, F., Vieu, P.:Nonparametric functional data analysis: theory and practice. Series in Statistics, Springer, New York (2006)Google Scholar
  4. 4.
    Ramsay, J. O., Silverman, B.W.: Functional Data Analysis (Second Edition). Springer Verlag, New York (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Frédéric Ferraty
    • 1
  • Adela Martínez-Calvo
    • 2
  • Philippe Vieu
    • 1
  1. 1.Institut de Mathématiques de ToulouseToulouseFrance
  2. 2.Universidade de Santiago de CompostelaSantiago de CompostelaSpain

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