Consistency of k-nearest Neighbor Regression Estimator under mixing condition with tie-breaking by randomization

Authors

  • Mohamed Deribati Tishreen University
  • Wafaa kanaan Tishreen University
  • Dema Al-shakh Tishreen University

Abstract

In most researches that have studied the consistency of nonparametric k-nearest neighbors estimator have been depended on tie breaking by indices strategy. We hope in this paper to study the regression function estimation by using nonparametric k-nearest neighbors estimation under strong mixing concept. Where the consistency results of k-nearest neighbor regression estimator in  have been expanded as independent case to the dependent case with using tie breaking by randomization instead of indices strategy.

 

Author Biographies

Mohamed Deribati, Tishreen University

Assistant Prof., Depart. Of Mathematical Statistics, Faculty of Science

Wafaa kanaan, Tishreen University

Prof., Depart. Of Mathematical Statistics, Faculty of Science

Dema Al-shakh, Tishreen University

Postgraduate student, Depart. Of Mathematical Statistics

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Published

2022-06-16

How to Cite

1.
محمد دريباتي, وفاء كنعان, ديمه الشاخ. Consistency of k-nearest Neighbor Regression Estimator under mixing condition with tie-breaking by randomization. TUJ-BA [Internet]. 2022Jun.16 [cited 2024Nov.24];44(2):115-2. Available from: https://journal.tishreen.edu.sy/index.php/bassnc/article/view/12725

Issue

Vol. 44 No. 2 (2022): Tishreen University Journal of Research and Scientific Studies - Basic Sciences Series

Section

Articles

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