A Random Matrix-Theoretic Approach to Handling Singular Covariance Estimates

In many practical situations we would like to estimate the covariance matrix of a set of variables from an insufficient amount of data. More specifically, if we have a set of N independent identically distributed measurements of an M dimensional random vector with N