6 papers
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…
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…
A general partial Cramér's condition for Edgeworth expansion of a function of sample means with applications
Yashi Wei, Jiang Hu, Zhidong Bai
A large class of statistics can be formulated as smooth functions of sample means of random vectors. In this paper, we propose a general partial Cramér's condition (GPCC) and appl…
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…
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…
On the rate of convergence in the CLT for LSS of large-dimensional sample covariance matrices
Jian Cui, Jiang Hu, Zhidong Bai +1
This paper investigates the rate of convergence for the central limit theorem of linear spectral statistic (LSS) associated with large-dimensional sample covariance matrices. We co…