The Berry-Esseen bound of a wavelet estimator in non-randomly designed nonparametric regression model based on ANA errors

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY

Esaim-Probability and Statistics Pub Date : 2020-01-01 DOI:10.1051/PS/2019017

Xu-fei Tang, Xuejun Wang, Yi Wu, Fei Zhang

引用次数: 1

Abstract

Consider the nonparametric regression model Y ni = g (t ni ) + e i , i = 1, 2, …, n , n ≥ 1, where e i , 1 ≤ i ≤ n , are asymptotically negatively associated (ANA, for short) random variables. Under some appropriate conditions, the Berry-Esseen bound of the wavelet estimator of g (⋅) is established. In addition, some numerical simulations are provided in this paper. The results obtained in this paper generalize some corresponding ones in the literature.

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基于ANA误差的非随机设计非参数回归模型中小波估计量的Berry-Esseen界

考虑非参数回归模型Y ni = g (t ni) + e i, i = 1,2，…，n, n≥1，其中e i, 1≤i≤n为渐近负相关(简称ANA)随机变量。在一定条件下，建立了g(⋅)的小波估计量的Berry-Esseen界。此外，本文还进行了数值模拟。本文所得结果推广了文献中相应的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Esaim-Probability and Statistics STATISTICS & PROBABILITY-

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

>12 weeks

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