6 citations · 13 across the 6 of their papers we have counts for
6 papers
Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when and applications
Jiaxin Qiu, Zeng Li, Jianfeng Yao
The asymptotic normality for a large family of eigenvalue statistics of a general sample covariance matrix is derived under the ultra-high dimensional setting, that is, when the di…
Provable More Data Hurt in High Dimensional Least Squares Estimator
Zeng Li, Chuanlong Xie, Qinwen Wang
This paper investigates the finite-sample prediction risk of the high-dimensional least squares estimator. We derive the central limit theorem for the prediction risk when both the…
Central Limit Theorem for Linear Spectral Statistics of Large Dimensional Kendall's Rank Correlation Matrices and its Applications
Zeng Li, Qinwen Wang, Runze Li
This paper is concerned with the limiting spectral behaviors of large dimensional Kendall's rank correlation matrices generated by samples with independent and continuous component…
Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model
Zeng Li, Fang Han, Jianfeng Yao
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 reg…
On testing for high-dimensional white noise
Zeng Li, Clifford Lam, Jianfeng Yao +1
Testing for white noise is a classical yet important problem in statistics, especially for diagnostic checks in time series modeling and linear regression. For high-dimensional tim…
Joint CLT for eigenvalue statistics from several dependent large dimensional sample covariance matrices with application
Weiming Li, Zeng Li, Jianfeng Yao
Let be a data matrix with complex-valued, independent and standardized entries satisfying a Lindeberg-type moment condition. We consider simult…