Confidence interval construction in massive data sets

被引：0
|
作者：
Song, Kai [1 ,2 ]
Xie, Xiaoyue [3 ]
Shi, Jian [1 ,4 ]
机构：
[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
[2] Beijing Inst Technol, Sch Management & Econ, Beijing, Peoples R China
[3] Air Force Engn Univ, Equipment Management & UAV Engn Coll, Xian, Peoples R China
[4] Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2024年 / 53卷 / 03期
关键词：
Confidence interval; coverage and length; divide and conquer; hypothesis testing; massive data; optimal local power;
D O I：
10.1080/03610926.2022.2100420
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：
This paper treats the problem of constructing confidence interval with massive data. Two methods using the divide and conquer strategy are proposed. The corresponding hypothesis testing problem is also developed. Theoretical and numerical results are presented to illustrate their effectiveness.
引用
收藏
页码：1035 / 1048
页数：14
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