We study the statistics of the largest eigenvalues of real symmetric and sample covariance matrices when the entries are heavy tailed. Extending the result obtained by Soshnikov in (Electron. Commun. Probab. 9 (2004) 82-91), we prove that, in the absence of the fourth moment, the asymptotic behavior of the top eigenvalues is determined by the behavior of the largest entries of the matrix. © 2009 Association des Publications de l'Institut Henri Poincaré.
CITATION STYLE
Auffinger, A., Arous, G. B., & Péchéb, S. (2009). Poisson convergence for the largest eigenvalues of heavy tailed random matrices. Annales de l’institut Henri Poincare (B) Probability and Statistics, 45(3), 589–610. https://doi.org/10.1214/08-AIHP188
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