On the rate of asymptotic normality of integral weighted kernel estimator in a non parametric regression model for φ-mixing random variables

Liwang Ding and Caoqing Jiang

Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 2, 604-619

Abstract: In this article, we study the convergence rate of asymptotic normality for the estimator in a non parametric regression model under φ-mixing random variables by using the blockwise technique. With different choices of the parameters, the rates are shown as O(n−1/9) and O(n−1/6). We also carry out some simulation studies and a real data analysis to support the theoretical results established here.

Date: 2025
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DOI: 10.1080/03610926.2024.2316261

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