dsDiscr

<p>Test dataset with only discrete variables.</p>

datasets

Performs efficient selection of high-dimensional undirected
graphical models as described in
Abreu, Edwards and Labouriau (2010) <doi:10.18637/jss.v037.i01>.
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.

Rodrigo Labouriau

gRapHD

Efficient Selection of Undirected Graphical Models for
High-Dimensional Datasets

dsDiscr function

<p>Data frame containing 200 observations and 20 variables.</p>

dsDiscr: Test dataset

Description

Arguments

Format

Examples