A Note on the Convergence of the Extreme Eigenvalues of a Large-Dimensional Sample Covariance Matrix
摘要
In this study, we explore both weak and strong convergence properties of extreme eigenvalues in a large-dimensional sample covariance matrix, specifically in cases where the data matrix comprises independent, though not identically distributed, elements. Our findings reveal that, provided there exists a uniform boundedness condition on the