Random Matrix Theory (RMT) has emerged as an indispensable framework for understanding the statistical properties of matrices whose entries are determined by probabilistic processes. Initially ...

The empirical determination of large covariance matrices is, however, fraught with difficulties and biases. But the vibrant field of random matrix theory (RMT) has provided original solutions to this ...

We place ourselves in the setting of high-dimensional statistical inference, where the number of variables p in a data set of interest is of the same order of magnitude as the number of observations n ...

The probability (Q) that the estimated between-group covariance matrix is not positive definite is computed for the balanced single classification multivariate analysis of variance with random effects ...