Package: gRapHD
Version: 0.2.6
Title: Efficient Selection of Undirected Graphical Models for
        High-Dimensional Datasets
Author: Gabriel Coelho Goncalves de Abreu <abreu_ga@yahoo.com.br>,
        Rodrigo Labouriau <rodrigo.labouriau@math.au.dk>,
        David Edwards <david.edwards@agrsci.dk>.
Maintainer: Rodrigo Labouriau <rodrigo.labouriau@math.au.dk>
Depends: R (>= 2.9.0), methods
Imports: graph
LazyLoad: yes
Description: 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.
License: GPL (>= 3)
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2018-02-06 16:05:57 UTC; rodrigo
Repository: CRAN
Date/Publication: 2018-02-06 17:40:23 UTC
