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We consider a class of real random matrices with dependent entries and show that the limiting empirical spectral distribution is given by the Marchenko-Pastur law.
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Götze, F.; Tikhomirov, A.; Limit Theorems for spectra of random matrices with martingale structure , Stein’s Method and Applications, Singapore Univ. Press (2005), pp. 181-195
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Adamczak, R., On the Marchenko-Pastur and circular laws for some classes of random matrices with dependent entries , Electronic Journal of Probability, Vol. 16 (2011)
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Bai, Z. D., Hu, J., Pan, G., Zhou, W., A Note on Rate of Convergence in Probability to Semicircular Law , Electronic Journal of Probability, Vol. 16(2011)
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Adamczak, R.; Litvak, A.; Pajor, A.; Tomczak-Jaegermann, N., Quantitative estimates of the convergence of the empirical covariance matrix in log-concave ensembles , J. Amer. Math. Soc. 23 (2010), 535-561
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Y. Q. Yin, P. R. Krishnaiah, Limit Theorem for the Eigenvalues of the Sample Covariance Matrix when the Underlying Distribution is Isotropic , Theory Probab. Appl. 30, pp. 861-867
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Bordenave, B., Caputo, P., Chafaï, D., Circular law theorem for random Markov matrices , Probability Theory and Related Fields, DOI 10.1007/s00440-010-0336-1 (2011)
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