Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach

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Somia Guenani , Wahiba Bouabsa, Mohammed Kadi Attouch

Abstract

We discuss in this paper the robust equivariant nonparametric regression estimators for strong mixing data with the k Nearest Neighbour (kNN) method. We consider a new robust regression estimator when the scale parameter is unknown. The principal aim is to prove the almost complete convergence (with rate) for the proposed estimator. Furthermore, a comparison study based on simulated data is also provided to illustrate the finite sample performances and the usefulness of the kNN approach.

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How to Cite
Somia Guenani , Wahiba Bouabsa, Mohammed Kadi Attouch. (2023). Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 14(2), 159–179. https://doi.org/10.17762/turcomat.v14i2.13635
Section
Research Articles