Extremal eigenvalues of sample covariance matrices with general population

Abstract

We consider the eigenvalues of sample covariance matrices of the form Q=(Σ1/2X)(Σ1/2X)∗. The sample X is an M×N rectangular random matrix with real independent entries and the population covariance matrix Σ is a positive definite diagonal matrix independent of X. Assuming that the limiting spectral density of Σ exhibits convex decay at the right edge of the spectrum, in the limit M,N→∞ with N/M→d∈(0,∞), we find a certain threshold d+ such that for d>d+ the limiting spectral distribution of Q also exhibits convex decay at the right edge of the spectrum. In this case, the largest eigenvalues of Q are determined by the order statistics of the eigenvalues of Σ, and in particular, the limiting distribution of the largest eigenvalue of Q is given by a Weibull distribution. In case d<d+, we also prove that the limiting distribution of the largest eigenvalue of Q is Gaussian if the entries of Σ are i.i.d. random variables. While Σ is considered to be random mostly, the results also hold for deterministic Σ with some additional assumptions.