Eigenvectors of Sample Covariance Matrices: Universality of Global Fluctuations

  • Published 2013


In this paper, we prove a universality result of convergence for a bivariate random process defined by the eigenvectors of a sample covariance matrix. Let Vn = (vij)i≤n, j≤m be a n ×m random matrix, where (n/m) → y > 0 as n → ∞, and let Xn = (1/m)VnV ∗ n be the sample covariance matrix associated to Vn . Consider the spectral decomposition of Xn given by… (More)


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