CRAN Task View: Graphical Models

Maintainer:Soren Hojsgaard
Contact:sorenh at

Wikipedia defines a graphical model as follows: A graphical model is a probabilistic model for which a graph denotes the conditional independence structure between random variables. They are commonly used in probability theory, statistics - particularly Bayesian statistics and machine learning.

A supplementary view is that graphical models are based on exploiting conditional independencies for constructing complex stochastic models with a modular structure. That is, a complex stochastic model is built up by simpler building blocks. This task view is a collection of packages intended to supply R code to deal with graphical models.

The packages can be roughly structured into the following topics (although several of them have functionalities which go across these categories):

Representation, manipulation and display of graphs

Classical models - General purpose packages

Miscellaneous: Model search, structure learning, specialized types of models etc.

Bayesian Networks/Probabilistic expert systems

BUGS models

CRAN packages:

Related links: