Bahadur representations for the bootstrap median absolute deviation and the application to projection depth weighted mean

被引：0
|
作者：
Liu, Qing [1 ,3 ]
Liu, Xiaohui [1 ,2 ]
Hu, Zihao [1 ,2 ]
机构：
[1] Jiangxi Univ Finance & Econ, Sch Stat & Data Sci, Nanchang 330013, Jiangxi, Peoples R China
[2] Jiangxi Univ Finance & Econ, Key Lab Data Sci Finance & Econ, Nanchang 330013, Jiangxi, Peoples R China
[3] Jiangxi Univ Finance & Econ, Res Ctr Appl Stat, Nanchang 330013, Jiangxi, Peoples R China
来源：
METRIKA | 2024年
基金：
中国博士后科学基金;
关键词：
Bootstrap MAD; Bootstrap projection depth weighted mean; Bahadur representation; QUANTILES;
D O I：
10.1007/s00184-024-00958-0
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Median absolute deviation (hereafter MAD) is known as a robust alternative to the ordinary variance. It has been widely utilized to induce robust statistical inferential procedures. In this paper, we investigate the strong and weak Bahadur representations of its bootstrap counterpart. As a useful application, we utilize the results to derive the weak Bahadur representation of the bootstrap sample projection depth weighted mean-a quite important location estimator depending on MAD.
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页数：24
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