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Extreme eigenvalue statistics of m-dependent heavy-tailed matrices

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arxiv 1910.08511 v3 pith:IHSZGF7M submitted 2019-10-18 math.PR

Extreme eigenvalue statistics of m-dependent heavy-tailed matrices

classification math.PR
keywords matriceseigenvalueentriesextremeheavy-tailedprocessstatisticsabove
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We analyze the largest eigenvalue statistics of m-dependent heavy-tailed Wigner matrices as well as the associated sample covariance matrices having entry-wise regularly varying tail distributions with parameter $0<\alpha<4$. Our analysis extends results in the previous literature for the corresponding random matrices with independent entries above the diagonal, by allowing for m-dependence between the entries of a given matrix. We prove that the limiting point process of extreme eigenvalues is a Poisson cluster process.

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