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Estimation of the noise covariance operator in functional linear regression with functional outputs

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  • Crambes, Christophe
  • Hilgert, Nadine
  • Manrique, Tito

Abstract

This work deals with the estimation of the noise in functional linear regression when both the response and the covariate are functional. Namely, we propose two estimators of the covariance operator of the noise. We give some asymptotic properties of these estimators, and we study their behavior on simulations.

Suggested Citation

  • Crambes, Christophe & Hilgert, Nadine & Manrique, Tito, 2016. "Estimation of the noise covariance operator in functional linear regression with functional outputs," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 7-15.
    • Handle: RePEc:eee:stapro:v:113:y:2016:i:c:p:7-15
    DOI: 10.1016/j.spl.2016.02.006
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    References listed on IDEAS

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    1. Cardot, Hervé & Ferraty, Frédéric & Sarda, Pascal, 1999. "Functional linear model," Statistics & Probability Letters, Elsevier, vol. 45(1), pages 11-22, October.
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    Cited by:

    1. Amel, Azzi & Ali, Laksaci & Elias, Ould Saïd, 2022. "On the robustification of the kernel estimator of the functional modal regression," Statistics & Probability Letters, Elsevier, vol. 181(C).

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