gRbase: A package for graphical modelling in R. The gRbase package provides certain general constructs which are used by other graphical modelling packages, in particular by the packages gRain, gRim and gRc. gRbase contains several datasets relevant for use in connection with graphical models. Almost all datasets used in the book Graphical Models with R (2012) are contained in gRbase. gRbase implements several graph algorithms (based mainly on representing graphs as adjacency matrices - either in the form of a standard matrix or a sparse matrix). Some graph algorithms are: (i) maximum cardinality search (for marked and unmarked graphs). (ii) moralize. (iii) triangulate. (iv) junctionTree. gRbase facilities for array operations, gRbase implements functions for testing for conditional independence. gRbase illustrates how hierarchical log-linear models (hllm) may be implemented and describes concept of gmData (graphical meta data). These features, however, are not maintained anymore and remains in gRbase only because there exists a paper describing these facilities: A Common Platform for Graphical Models in R: The gRbase Package, Journal of Statistical Software, Vol 14, No 17, 2005.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Bontempi, Gianluca; Flauder, Maxime: From dependency to causality: a machine learning approach (2015)
- Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2015)
- Marco Scutari: Learning Bayesian Networks with the bnlearn R Package (2009) arXiv