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Sample Covariance Matrix for Random Vectors with Heavy Tails
Authors:Mark M. Meerschaert  Hans-Peter Scheffler
Affiliation:(1) Department of Mathematics, University of Nevada, Reno, Nevada, 89557;(2) Department of Mathematics, University of Dortmund, 44221 Dortmund, Germany
Abstract:We compute the asymptotic distribution of the sample covariance matrix for independent and identically distributed random vectors with regularly varying tails. If the tails of the random vectors are sufficiently heavy so that the fourth moments do not exist, then the sample covariance matrix is asymptotically operator stable as a random element of the vector space of symmetric matrices.
Keywords:Operator stable  generalized domains of attraction  regular variation  sample covariance matrix  heavy tails
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