Estimating the covariance of random matrices

Pierre Youssef

doi:10.1214/EJP.v18-2579

Estimating the covariance of random matrices

Pierre Youssef

Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

We extend to the matrix setting a recent result of Srivastava-Vershynin [24] about estimating the covariance matrix of a random vector. The result can be interpreted as a quantified version of the law of large numbers for positive semi-definite matrices which verify some regularity assumption. Beside giving examples, we discuss the notion of log-concave matrices and give estimates on the smallest and largest eigenvalues of a sum of such matrices.

Original language	English (US)
Article number	107
Journal	Electronic Journal of Probability
Volume	18
DOIs	https://doi.org/10.1214/EJP.v18-2579
State	Published - Dec 19 2013

Keywords

Covariance matrix
Log-concave matrix

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1214/EJP.v18-2579

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Estimating the covariance of random matrices

Abstract

Keywords

ASJC Scopus subject areas

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