A Random Matrix--Theoretic Approach to Handling Singular Covariance Estimates

Details A Random Matrix--Theoretic Approach to Handling Singular Covariance Estimates A Random Matrix--Theoretic Approach to Handling Singular Covariance Estimates

2010-10-04

arxiv.org/abs/1010.0601v1

Mathematics

Probability

Submitted to Transactions on Information Theory

Scientific paper

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 the maximum likelihood estimate is the sample covariance matrix. Here we consider the case where $N

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