Graphical Independence Networks with the gRain Package for R

Abstract

In this paper we present the R package gRain for propagation in graphical independence networks (for which Bayesian networks is a special instance). The paper includes a description of the theory behind the computations. The main part of the paper is an illustration of how to use the package. The paper also illustrates how to turn a graphical model and data into an independence network

Keywords

• conditional independence
• conditional probability
• directed acyclical graph
• evidence
• expert system
• graph
• graphical model
• junction tree
• maximum cardinality search
• message passing
• running intersection property
• triangulation