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November 2010 Concentration of empirical distribution functions with applications to non-i.i.d. models
S.G. Bobkov, F. Götze
Bernoulli 16(4): 1385-1414 (November 2010). DOI: 10.3150/10-BEJ254

Abstract

The concentration of empirical measures is studied for dependent data, whose joint distribution satisfies Poincaré-type or logarithmic Sobolev inequalities. The general concentration results are then applied to spectral empirical distribution functions associated with high-dimensional random matrices.

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S.G. Bobkov. F. Götze. "Concentration of empirical distribution functions with applications to non-i.i.d. models." Bernoulli 16 (4) 1385 - 1414, November 2010. https://doi.org/10.3150/10-BEJ254

Information

Published: November 2010
First available in Project Euclid: 18 November 2010

zbMATH: 1207.62106
MathSciNet: MR2759184
Digital Object Identifier: 10.3150/10-BEJ254

Keywords: empirical measures , logarithmic Sobolev inequalities , Poincaré-type inequalities , random matrices , spectral distributions

Rights: Copyright © 2010 Bernoulli Society for Mathematical Statistics and Probability

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Vol.16 • No. 4 • November 2010
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