  Many modern statistical applications ask for the estimation of a covariance
(or precision) matrix in settings where the number of variables is larger than
the number of observations. There exists a broad class of ridge-type estimators
that employs regularization to cope with the subsequent singularity of the
sample covariance matrix. These estimators depend on a penalty parameter and
choosing its value can be hard, in terms of being computationally unfeasible or
tenable only for a restricted set of ridge-type estimators. Here we introduce a
simple graphical tool, the spectral condition number plot, for informed
heuristic penalty parameter selection. The proposed tool is computationally
friendly and can be employed for the full class of ridge-type covariance
(precision) estimators.
