activity
20082026
most citedUniversality for the largest eigenvalue of sample covariance matrices with general population

101 citations · 322 across the 19 of their papers we have counts for

collaborators

20 papers

math.ST2026

When is Hotelling's asymptotically -distributed?

Yanpeng Li, Guangming Pan, Wang Zhou

For Gaussian observations, a deterministic multiple of Hotelling's statistic has an exact distribution. This paper investigates when this approximation remains valid for…

math.ST2026★ 2 cited

Spectral Analysis of Gram Matrices with Missing at Random Observations: Convergence, Central Limit Theorems, and Applications in Statistical Inference

Huiqin Li, Guangming Pan, Yanqing Yin +1

Motivated by the statistical inference using the Gram matrix in the context of missing at random observations, this paper investigates the spectral properties of the random matrice…

math.PR2024

Necessary and sufficient condition for CLT of linear spectral statistics of sample correlation matrices

Yanpeng Li, Guangming Pan, Jiahui Xie +1

In this paper, we establish the central limit theorem (CLT) for the linear spectral statistics (LSS) of sample correlation matrix , constructed from a data matrix $X…

math.ST2023★ 2 cited

Asymptotic limits of spiked eigenvalues and eigenvectors of signal-plus-noise matrices with weak signals and heteroskedastic noise

Xiaoyu Liu, Yiming Liu, Guangming Pan +2

This paper is to study a signal-plus-noise model in high dimensional settings when the dimension and the sample size are comparable. Specifically, we assume that the noise has a ge…

math.ST2022

CLT for random quadratic forms based on sample means and sample covariance matrices

Wenzhi Yang, Yiming Liu, Guangming Pan +1

In this paper, we use the dimensional reduction technique to study the central limit theory (CLT) random quadratic forms based on sample means and sample covariance matrices. Speci…

cs.CV2021

Spectral Machine Learning for Pancreatic Mass Imaging Classification

Yiming Liu, Ying Chen, Guangming Pan +5

We present a novel spectral machine learning (SML) method in screening for pancreatic mass using CT imaging. Our algorithm is trained with approximately 30,000 images from 250 pati…