期刊
ANNALS OF STATISTICS
卷 48, 期 6, 页码 3138-3160出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/19-AOS1882
关键词
Generalized spiked model; asymptotic distribution; extreme eigenvalues; trace; large sample covariance matrix; random matrix theory
资金
- NSF [DMS-1712536]
- Hong Kong RGC [GRF-17306918]
- NSFC (National Natural Science Foundation of China) [12031005]
This paper studies the joint limiting behavior of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model, where the asymptotic regime is such that the dimension and sample size grow proportionally. The form of the joint limiting distribution is applied to conduct Johnson-Graybill-type tests, a family of approaches testing for signals in a statistical model. For this, higher order correction is further made, helping alleviate the impact of finite-sample bias. The proof rests on determining the joint asymptotic behavior of two classes of spectral processes, corresponding to the extreme and linear spectral statistics, respectively.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据