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Functional Statistics and Related Fields pp 161–167Cite as

Uniform in the smoothing parameter consistency results in functional regression

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Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

This paper focuses on uniform in bandwidth and uniform in nearest neighbors consistencies of both kernel and kNN type estimators involving functional data. We established in previous works results in this topic for a selection of nonparametric conditional operators. Our interest here is to adapt that approach for studying the generalized nonparametric regression function.

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References

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Author information

Authors and Affiliations

  1. Université Djillali Liabés, LSPS, Sidi Bel Abbés, Algeria

    Lydia Kara-Zaïtri & Ali Laksaci

  2. Université Grenoble Alpes, AGIM Team, AGEIS, EA 7407, Grenoble, France

    Mustapha Rachdi

  3. Université Paul-Sabatier, IMT, Toulouse, France

    Philippe Vieu

Authors
  1. Lydia Kara-Zaïtri
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  2. Ali Laksaci
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  3. Mustapha Rachdi
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  4. Philippe Vieu
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Corresponding author

Correspondence to Lydia Kara-Zaïtri .

Editor information

Editors and Affiliations

  1. Dept. of Mathematics, University of A Coruña, A Coruña, Spain

    Germán Aneiros

  2. Dept. of Studies in Econ.and Business, University of Eastern Piedmont "Amedeo Avogadro", Novara, Italy

    Enea G. Bongiorno

  3. Dept. of Mathematics, University of A Coruña, A Coruña, Spain

    Ricardo Cao

  4. Toulouse Mathematics Institute (IMT), Paul Sabatier University, Toulouse, France

    Philippe Vieu

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Kara-Zaïtri, L., Laksaci, A., Rachdi, M., Vieu, P. (2017). Uniform in the smoothing parameter consistency results in functional regression. In: Aneiros, G., G. Bongiorno, E., Cao, R., Vieu, P. (eds) Functional Statistics and Related Fields. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-55846-2_21

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