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<p>In this paper, we investigate the strong uniform consistency rate of the Nadaraya-Watson (NW) kernel regression estimator under a widely orthant dependence model. The performance of the proposed estimator is illustrated through some simulations. Furthermore, a large comparison study with other NW estimators is presented based on the selected bandwidth type, and the performance of these NW estimators is evaluated using the global mean squared error (GMSE) criterion. Moreover, a real data analysis is provided to support the theoretical results.</p>

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Convergence rate of the Nadaraya-Watson kernel regression estimator under widely orthant dependent sequences

  • 期刊论文

  • 发表日期：

    2026年5月11日

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  • Mohamed Kaber El Alem,
  • Zohra Guessoum,
  • Abdelkader Tatachak

摘要

In this paper, we investigate the strong uniform consistency rate of the Nadaraya-Watson (NW) kernel regression estimator under a widely orthant dependence model. The performance of the proposed estimator is illustrated through some simulations. Furthermore, a large comparison study with other NW estimators is presented based on the selected bandwidth type, and the performance of these NW estimators is evaluated using the global mean squared error (GMSE) criterion. Moreover, a real data analysis is provided to support the theoretical results.