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math.ST2026

Functional CLT for general sample covariance matrices

Jian Cui, Zhijun Liu, Jiang Hu +1

This paper studies the central limit theorems (CLTs) for linear spectral statistics (LSSs) of general sample covariance matrices, when the test functions belong to , the class…

math.ST2025

Asymptotics for Reinforced Stochastic Processes on Hierarchical Networks

Li Yang, Dandan Jiang, Jiang Hu +1

In this paper, we analyze the asymptotic behavior of a system of interacting reinforced stochastic processes on a directed network of agents. The sys…

math.ST2025

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model

Zhijun Liu, Jiang Hu, Zhidong Bai +1

In this paper, we establish the Central Limit Theorem (CLT) for linear spectral statistics (LSSs) of large-dimensional generalized spiked sample covariance matrices, where the spik…

math.ST2025

Edgeworth corrections for the spiked eigenvalues of non-Gaussian sample covariance matrices with applications

Yashi Wei, Jiang Hu, Zhidong Bai

Yang and Johnstone (2018) established an Edgeworth correction for the largest sample eigenvalue in a spiked covariance model under the assumption of Gaussian observations, leaving…

math.ST2024

Asymptotic properties of a multicolored random reinforced urn model with an application to multi-armed bandits

Li Yang, Jiang Hu, Jianghao Li +1

The random self-reinforcement mechanism, characterized by the principle of ``the rich get richer'', has demonstrated significant utility across various domains. One prominent model…

math.ST2024

The Asymptotic Properties of the Extreme Eigenvectors of High-dimensional Generalized Spiked Covariance Model

Zhangni Pu, Xiaozhuo Zhang, Jiang Hu +1

In this paper, we investigate the asymptotic behaviors of the extreme eigenvectors in a general spiked covariance matrix, where the dimension and sample size increase proportionall…