Berry–Esseen bounds for wavelet estimator in a regression model with linear process errors

In this paper, we derive the Berry–Esseen bounds of the wavelet estimator for a nonparametric regression model with linear process errors generated by φφ-mixing sequences. As application, by the suitable choice of some constants, the convergence rate O(n−1/6)O(n−1/6) of uniformly asymptotic normality of the wavelet estimator is obtained. Our results generalize some known results in the literature.