  The properties of penalized sample covariance matrices depend on the choice
of the penalty function. In this paper, we introduce a class of non-smooth
penalty functions for the sample covariance matrix, and demonstrate how this
method results in a grouping of the estimated eigenvalues. We refer to this
method as "lassoing eigenvalues" or as the "elasso".
