Smitha Ankinakatte <Smitha.AA@agrsci.dk> and David Edwards <David.Edwards@agrsci.dk>
gRapfa is for modelling discrete longitudinal data using acyclic probabilistic finite automata (APFA). The package contains functions for constructing APFA models from a given data using penalized likelihood methods. For graphical display of APFA models, gRapfa depends on 'igraph package'. gRapfa also contains an interface function to Beagle software that implements an efficient model selection algorithm.

gRbase - a package for graphical modelling in R
Søren Højsgaard <sorenh@agrsci.dk>, Claus Dethlefsen
<dethlef@math.aau.dk> and the rest of the Danish gR group
This package defines S4-classes gmData (graphical meta data), gModel (graphical model) and illustrates how hierarchical log-linear models (hllm) may be implemented and combined with dynamicGraph.

Søren Højsgaard <sorenh@agrsci.dk>, Claus Dethlefsen
<dethlef@math.aau.dk>, David Edwards <ded@novonordisk.com>
zzz.R formulae.R hll.R validVarTypes.R gmData.R gModel.R modify.R loadgRbasehllm.R loadgRbaseDynamic.R dynamicGraph.R

Søren Højsgaard <sorenh@agrsci.dk>, Claus Dethlefsen
<aas.claus.dethlefsen@nja.dk>
This package defines S3-classes gmData (graphical meta data), gModel (graphical model) and illustrates how hierarchical log-linear models (hllm) may be implemented and combined with dynamicGraph.

R (>= 2.1.0), MASS, dynamicGraph,methods

Søren Højsgaard <sorenh@agrsci.dk>, Claus Dethlefsen <cld@rn.dk>
This package defines S3-classes gmData (graphical meta data), gModel (graphical model) and illustrates how hierarchical log-linear models (hllm) may be implemented.

This package defines S3-classes gmData (graphical meta data), gModel (graphical model). Several other graphical modelling packages rely on these fundamental constructs. gRbase illustrates how hierarchical log-linear models (hllm) may be implemented.

The gRbase package provides certain general constructs which are used by other graphical modelling packages. This includes 1) the concept of gmData (graphical meta data), 2) several graph algorithms 3) facilities for table operations, 4) functions for testing for conditional independence. gRbase also illustrates how hierarchical log-linear models (hllm) may be implemented.