Efficient selection of undirected graphical models for
high-dimensional datasets
Description
gRapHD is designed for efficient selection of
high-dimensional undirected graphical models. The package
provides tools for selecting trees, forests and decomposable
models minimizing information criteria such as AIC or BIC, and
for displaying the independence graphs of the models. It has
also some useful tools for analysing graphical structures. It
supports the use of discrete, continuous, or both types of
variables.