87 citations · 310 across the 25 of their papers we have counts for
11 papers · 1 filter
Factor Modelling for Clustering High-dimensional Time Series
Bo Zhang, Guangming Pan, Qiwei Yao +1
We propose a new unsupervised learning method for clustering a large number of time series based on a latent factor structure. Each cluster is characterized by its own cluster-spec…
Tracy-Widom law for the extreme eigenvalues of large signal-plus-noise matrices
Zhixiang Zhang, Guangming Pan
Let $\bY =\bR+\bX$ be an matrix, where $\bR$ is a rectangular diagonal matrix and $\bX$ consists of entries. This is a signal-plus-noise type model. Its signal…
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…
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…
Homoscedasticity tests for both low and high-dimensional fixed design regressions
Zhidong Bai, Guangming Pan, Yanqing Yin
This paper is to prove the asymptotic normality of a statistic for detecting the existence of heteroscedasticity for linear regression models without assuming randomness of covaria…