Efficient computation of limit spectra of sample covariance matrices
Efficient computation of limit spectra of sample covariance matrices
Consider an $n \times p$ data matrix $X$ whose rows are independently sampled from a population with covariance $\Sigma$. When $n,p$ are both large, the eigenvalues of the sample covariance matrix are substantially different from those of the true covariance. Asymptotically, as $n,p \to \infty$ with $p/n \to \gamma$, there …