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: |
0.2.4 |
| Depends: |
R (≥ 2.9.0), methods, graph |
| Published: |
2014-03-09 |
| 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: