activity
20172022
most citedEstimating Number of Factors by Adjusted Eigenvalues Thresholding

24 citations · 35 across the 7 of their papers we have counts for

collaborators

7 papers

stat.ME2022

Adaptive Tests for Bandedness of High-dimensional Covariance Matrices

Xiaoyi Wang, Gongjun Xu, Shurong Zheng

Estimation of the high-dimensional banded covariance matrix is widely used in multivariate statistical analysis. To ensure the validity of estimation, we aim to test the hypothesis…

stat.ME20221 cited

On block-wise and reference panel-based estimators for genetic data prediction in high dimensions

Bingxin Zhao, Shurong Zheng, Hongtu Zhu

Genetic prediction of complex traits and diseases has attracted enormous attention in precision medicine, mainly because it has the potential to translate discoveries from genome-w…

math.ST20201 cited

Asymptotic independence of spiked eigenvalues and linear spectral statistics for large sample covariance matrices

Zhixiang Zhang, Shurong Zheng, Guangming Pan +1

We consider general high-dimensional spiked sample covariance models and show that their leading sample spiked eigenvalues and their linear spectral statistics are asymptotically i…

stat.ME201924 cited

Estimating Number of Factors by Adjusted Eigenvalues Thresholding

Jianqing Fan, Jianhua Guo, Shurong Zheng

Determining the number of common factors is an important and practical topic in high dimensional factor models. The existing literatures are mainly based on the eigenvalues of the…

math.ST20194 cited

Community Detection Based on the convergence of eigenvectors in DCBM

Yan Liu, Zhiqiang Hou, Zhigang Yao +3

Spectral clustering is one of the most popular algorithms for community detection in network analysis. Based on this rationale, in this paper we give the convergence rate of eigenv…

math.ST20191 cited

Central limit theorem for linear spectral statistics of general separable sample covariance matrices with applications

Huiqin Li, Yanqing Yin, Shurong Zheng

In this paper, we consider the separable covariance model, which plays an important role in wireless communications and spatio-temporal statistics and describes a process where the…