gRapHD: Efficient selection of undirected graphical models for
high-dimensional datasets
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.
| Version: |
0.2.3 |
| Depends: |
R (≥ 2.9.0), methods |
| Imports: |
graph |
| Suggests: |
graph |
| Published: |
2013-04-14 |
| Author: |
Gabriel Coelho Goncalves de Abreu,
Rodrigo Labouriau, David Edwards. |
| Maintainer: |
Gabriel Coelho Goncalves de Abreu <abreu_ga at yahoo.com.br> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
yes |
| Citation: |
gRapHD citation info |
| In views: |
gR |
| CRAN checks: |
gRapHD results |
Downloads: