A CLT for the LSS of large-dimensional sample covariance matrices with diverging spikes
含发散尖峰的大维样本协方差矩阵线性谱统计量的中心极限定理
In this paper, we establish the central limit theorem (CLT) for linear spectral statistics (LSSs) of a large-dimensional sample covariance matrix when the population covariance matrices are involved with diverging spikes. This constitutes a nontrivial extension of the Bai–Silverstein theorem (BST) (Ann. Probab. 32 (2004) 553–605), a theorem that has strongly influenced the development of high-dimensional statistics, especially in the applications of random matrix theory to…