16 citations · 23 across the 4 of their papers we have counts for
5 papers
Universal Rank Inference via Residual Subsampling with Application to Large Networks
Xiao Han, Qing Yang, Yingying Fan
Determining the precise rank is an important problem in many large-scale applications with matrix data exploiting low-rank plus noise models. In this paper, we suggest a universal…
SIMPLE: Statistical Inference on Membership Profiles in Large Networks
Jianqing Fan, Yingying Fan, Xiao Han +1
Network data is prevalent in many contemporary big data applications in which a common interest is to unveil important latent links between different pairs of nodes. Yet a simple f…
Limiting Laws for Divergent Spiked Eigenvalues and Largest Non-spiked Eigenvalue of Sample Covariance Matrices
Tony Cai, Xiao Han, Guangming Pan
We study the asymptotic distributions of the spiked eigenvalues and the largest nonspiked eigenvalue of the sample covariance matrix under a general covariance matrix model with di…
A unified matrix model including both CCA and F matrices in multivariate analysis: the largest eigenvalue and its applications
Xiao Han, Guangming Pan, Qing Yang
Let $\bbZ_{M_1\times N}=\bbT^{\frac{1}{2}}\bbX$ where $(\bbT^{\frac{1}{2}})^2=\bbT$ is a positive definite matrix and $\bbX$ consists of independent random variables with mean zero…
High Dimensional Correlation Matrices: CLT and Its Applications
Jiti Gao, Xiao Han, Guangming Pan +1
Statistical inferences for sample correlation matrices are important in high dimensional data analysis. Motivated by this, this paper establishes a new central limit theorem (CLT)…