Testing the independence of sets of large-dimensional variables

被引:0
|
作者
DanDan Jiang
ZhiDong Bai
ShuRong Zheng
机构
[1] Jilin University,School of Mathematics
[2] Northeast Normal University,KLAS and School of Mathematics and Statistics
来源
Science China Mathematics | 2013年 / 56卷
关键词
large-dimensional data analysis; independence test; random ; -matrices; 15A52; 62H15; 60F05; 62E20; 15A18;
D O I
暂无
中图分类号
学科分类号
摘要
This paper proposes the corrected likelihood ratio test (LRT) and large-dimensional trace criterion to test the independence of two large sets of multivariate variables of dimensions p1 and p2 when the dimensions p = p1 + p2 and the sample size n tend to infinity simultaneously and proportionally. Both theoretical and simulation results demonstrate that the traditional χ2 approximation of the LRT performs poorly when the dimension p is large relative to the sample size n, while the corrected LRT and large-dimensional trace criterion behave well when the dimension is either small or large relative to the sample size. Moreover, the trace criterion can be used in the case of p > n, while the corrected LRT is unfeasible due to the loss of definition.
引用
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页码:135 / 147
页数:12
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