Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Provides statistical tools for Bayesian structure learning in undirected graphical models with both continuous and discrete variables.


News

  • CHANGES IN VERSION 2.19 The Title in Description is changed Function "I.g" is added

  • CHANGES IN VERSION 2.20 Reversible jump MCMC algorithm is added to "bdgraph()" fonction

  • CHANGES IN VERSION 2.23 Function "I.g" is chenged to "log_Ig" and it is implemented in C++

  • CHANGES IN VERSION 2.24 Function "phat" is changed to "plinks" Function "prob" is changed to "pgraph" Function "log_Ig" is changed to "gnorm"

  • CHANGES IN VERSION 2.28 The Title in Description is changed Function "bdgraph.ts", "rgcwish", and "rcwish" are added to the package

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("BDgraph")

2.33 by Abdolreza Mohammadi, 9 days ago


https://www.tilburguniversity.edu/webwijs/show/a.mohammadi.htm


Browse source code at https://github.com/cran/BDgraph


Authors: Abdolreza Mohammadi and Ernst Wit


Documentation:   PDF Manual  


Task views: gRaphical Models in R


GPL (>= 2) license


Depends on Matrix, igraph


See at CRAN