Converges in of nearest neighbor regression function estimate for strong mixing processes

Authors

  • Mohamed M. Deribati Tishreen University
  • Ahmad Younso Damascus University
  • Dema Al-shakh Tishreen University

Abstract

In this paper, we will study the issue of estimating regression function using k-nearest neighbors method (knn) for  mixing processes. We will extend the convergence in  for knn regression from independent case to the dependent case; In addition, we will conduct a simulation study using R software program to display the importance and influence of choosing number of neighbors (k) and the sample size (n) on behavior of the estimator. For this purpose, the mean squares error criterion (MSE) was used. The high variability of the MSE results shows that knn estimators are very sensitive to the choice of the number of neighbors. More results show that the higher value of n, the more accurate and effective the estimator.

Author Biographies

Mohamed M. Deribati, Tishreen University

Associate Professor, Depart. Of Mathematical Statistics, Faculty of Science

 

Ahmad Younso, Damascus University

Associate Professor, Depart. Of Mathematical Statistics, Faculty of Science

 

Dema Al-shakh, Tishreen University

Postgraduate student, Depart. Of Mathematical Statistics

 

Downloads

Published

2022-01-15

How to Cite

1.
دريباتي مم, يونسو ا, الشاخ د. Converges in of nearest neighbor regression function estimate for strong mixing processes. TUJ-BA [Internet]. 2022Jan.15 [cited 2024Apr.19];43(6):59-71. Available from: https://journal.tishreen.edu.sy/index.php/bassnc/article/view/11509

Issue

Vol. 43 No. 6 (2021): Tishreen University Journal of Research and Scientific Studies - Basic Sciences Series

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The authors retain the copyright and grant the right to publish in the magazine for the first time with the transfer of the commercial right to the Tishreen University Journal -Basic Sciences Series  

 Under a CC BY- NC-SA 04 license that allows others to share the work with of the work's authorship and initial publication in this journal. Authors can use a copy of their articles in their scientific activity, and on their scientific websites, provided that the place of publication is indicted in Tishreen University Journal -Basic Sciences Series .  The Readers have the right to send, print and subscribe to the initial version of the article, and the title of Tishreen University Journal -Basic Sciences Series   Publisher

 

journal uses a CC BY-NC-SA license which mean

You are free to:

  • Adapt — remix, transform, and build upon the material
  •  
  • The licensor cannot revoke these freedoms as long as you follow the license terms.

 

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • NonCommercial — You may not use the material for commercial purposes.
  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.