  This article describes the R package varrank. It has a flexible
implementation of heuristic approaches which perform variable ranking based on
mutual information. The package is particularly suitable for exploring
multivariate datasets requiring a holistic analysis. The core functionality is
a general implementation of the minimum redundancy maximum relevance (mRMRe)
model. This approach is based on information theory metrics. It is compatible
with discrete and continuous data which are discretised using a large choice of
possible rules. The two main problems that can be addressed by this package are
the selection of the most representative variables for modeling a collection of
variables of interest, i.e., dimension reduction, and variable ranking with
respect to a set of variables of interest.
