We extend to the matrix setting a recent result of Srivastava-Vershynin  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.
- Covariance matrix
- Log-concave matrix
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty