Open Access
ARTICLE
The k Nearest Neighbors Estimator of the M-Regression in Functional Statistics
Ahmed Bachir1, *, Ibrahim Mufrah Almanjahie1, 2, Mohammed Kadi Attouch3
1 Department of Mathematics, College of Science, King Khalid University, Abha, 62529, Saudi Arabia.
2 Statistical Research and Studies Support Unit, King Khalid University, Abha, 62529, Saudi Arabia.
3 Djillali Liabes University, Sidi Belabbes, 22000, Algeria.
* Corresponding Authors: Ahmed Bachir. Email: ; .
Computers, Materials & Continua 2020, 65(3), 2049-2064. https://doi.org/10.32604/cmc.2020.011491
Received 11 May 2020; Accepted 19 August 2020; Issue published 16 September 2020
Abstract
It is well known that the nonparametric estimation of the regression function is
highly sensitive to the presence of even a small proportion of outliers in the data. To solve
the problem of typical observations when the covariates of the nonparametric component
are functional, the robust estimates for the regression parameter and regression operator
are introduced. The main propose of the paper is to consider data-driven methods of
selecting the number of neighbors in order to make the proposed processes fully automatic.
We use the
Keywords
Cite This Article
APA Style
Bachir, A., Almanjahie, I.M., Attouch, M.K. (2020). The k nearest neighbors estimator of the m-regression in functional statistics. Computers, Materials & Continua, 65(3), 2049-2064. https://doi.org/10.32604/cmc.2020.011491
Vancouver Style
Bachir A, Almanjahie IM, Attouch MK. The k nearest neighbors estimator of the m-regression in functional statistics. Comput Mater Contin. 2020;65(3):2049-2064 https://doi.org/10.32604/cmc.2020.011491
IEEE Style
A. Bachir, I.M. Almanjahie, and M.K. Attouch "The k Nearest Neighbors Estimator of the M-Regression in Functional Statistics," Comput. Mater. Contin., vol. 65, no. 3, pp. 2049-2064. 2020. https://doi.org/10.32604/cmc.2020.011491
Citations