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The scalar-on-function modal regression for functional time series data

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  • Amel Azzi
  • Abderrahmane Belguerna
  • Ali Laksaci
  • Mustapha Rachdi

Abstract

This paper develops a new nonparametric estimator of the scalar-on function modal regression that is used to analyse the co-variability between a functional regressor and a scalar output variable. The new estimator inherits the smoothness of the kernel method and the robustness of the quantile regression. We assume that the functional observations are structured as a strong mixing functional time series data and we establish the almost complete consistency (with rate) of the constructed estimator. A discussion highlighting the impact of this new estimator in nonparametric functional data analysis is also given. The usefulness of this new estimator is shown using an artificial data example.

Suggested Citation

  • Amel Azzi & Abderrahmane Belguerna & Ali Laksaci & Mustapha Rachdi, 2024. "The scalar-on-function modal regression for functional time series data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 36(2), pages 503-526, April.
    • Handle: RePEc:taf:gnstxx:v:36:y:2024:i:2:p:503-526
    DOI: 10.1080/10485252.2023.2233642
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