Article
Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach
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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.
Keywords
Functional data, ergodic data, kNN estimation, kernel estimate, uniform almost complete convergence rate, entropy
Citation
Guenani, S., Bouabsa, W., & Attouch, M. K. (2023). Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach. Turkish Journal of Computer and Mathematics Education, 14(2), 159–179.
S. Guenani, W. Bouabsa and M. K. Attouch, “Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach,” Turkish Journal of Computer and Mathematics Education, vol. 14, no. 2, pp. 159–179, 2023.
Guenani S, Bouabsa W, Attouch MK. Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach. Turkish Journal of Computer and Mathematics Education. 2023;14(2):159–179.
Guenani, S., Bouabsa, W. and Attouch, M. K. (2023), ‘Robust equivariant nonparametric regression estimators for strongly mixing data using a k nearest neighbour approach’, Turkish Journal of Computer and Mathematics Education, 14(2), pp. 159–179.
Guenani, Somia, et al. “Robust Equivariant Nonparametric Regression Estimators for Strongly Mixing Data Using a K Nearest Neighbour Approach.” Turkish Journal of Computer and Mathematics Education, vol. 14, no. 2, 2023, pp. 159–179.
Guenani, Somia, Wahiba Bouabsa, and Mohammed Kadi Attouch. “Robust Equivariant Nonparametric Regression Estimators for Strongly Mixing Data Using a K Nearest Neighbour Approach.” Turkish Journal of Computer and Mathematics Education 14, no. 2 (2023): 159–179.
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Published by: Engineering Journals


