BDgraph (2.15)

Graph Estimation Based on Birth-Death MCMC Approach.

This package provides a general framework to perform Bayesian structure learning in undirected graphical models. The package provides recent improvements in the Bayesian literature. The package consists of two main MCMC sampling algorithm efficiently implemented in C++ to maximize computational speed. The main target of the package is high-dimensional data analysis wherein either continuous or discrete variables and usually number of variables are less than number of observations. Acknowledgements: The help of the CRAN team to integrate C++ code with R is gratefully acknowledged.

Maintainer: Abdolreza Mohammadi
Author(s): Abdolreza Mohammadi and Ernst Wit

License: GPL (>= 3)

Uses: Does not use any package
Reverse depends: bmixture, ssgraph
Reverse suggests: BayesSUR

Released almost 5 years ago.