activity
20142025
most citedCLT for large dimensional general Fisher matrices and its applications in high-dimensional data analysis

3 citations · 11 across the 17 of their papers we have counts for

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Showing math.PRShow all

5 papers · 1 filter

math.PR2025

On the rate of convergence in the CLT for LSS of large-dimensional sample covariance matrices

Jian Cui, Jiang Hu, Zhidong Bai +1

This paper investigates the rate of convergence for the central limit theorem of linear spectral statistic (LSS) associated with large-dimensional sample covariance matrices. We co…

math.PR2024

A revisit of the circular law

Zhidong Bai, Jiang Hu

Consider a complex random matrix , whose entries are independent random variables with zero means and unit variances. It is wel…

math.PR2023

Exact Separation of Eigenvalues of Large Dimensional Noncentral Sample Covariance Matrices

Zhidong Bai, Jiang Hu, Jack W. Silverstein +1

Let $ \bbB_n =\frac{1}{n}(\bbR_n + \bbT^{1/2}_n \bbX_n)(\bbR_n + \bbT^{1/2}_n \bbX_n)^* $ where $ \bbX_n $ is a matrix with independent standardized random variables…

math.PR2023

No Eigenvalues Outside the Support of the Limiting Spectral Distribution of Large Dimensional noncentral Sample Covariance Matrices

Zhidong Bai, Jiang Hu, Jack W. Silverstein +1

Let $ \bbB_n =\frac{1}{n}(\bbR_n + \bbT^{1/2}_n \bbX_n)(\bbR_n + \bbT^{1/2}_n \bbX_n)^* $, where $ \bbX_n $ is a matrix with independent standardized random variable…

math.PR20162 cited

Central limit theorem for linear spectral statistics of large dimensional separable sample covariance matrices

Bai Zhidong, Li Huiqin, Pan Guangming

Suppose that is whose elements are independent real variables with mean zero, variance 1 and the fourth moment equal to three. The separable samp…