Create and learn Chain Event Graph (CEG) models using a Bayesian framework. It provides us with a Hierarchical Agglomerative algorithm to search the CEG model space. The package also includes several facilities for visualisations of the objects associated with a CEG. The CEG class can represent a range of relational data types, and supports arbitrary vertex, edge and graph attributes. A Chain Event Graph is a tree-based graphical model that provides a powerful graphical interface through which domain experts can easily translate a process into sequences of observed events using plain language. CEGs have been a useful class of graphical model especially to capture context-specific conditional independences. References: Collazo R, Gorgen C, Smith J. Chain Event Graph. CRC Press, ISBN 9781498729604, 2018 (forthcoming); and Barday LM, Collazo RA, Smith JQ, Thwaites PA, Nicholson AE. The Dynamic Chain Event Graph. Electronic Journal of Statistics, 9 (2) 2130-2169 <doi:10.1214/15-EJS1068>.
Version: | 0.1.0 |
Depends: | R (≥ 3.2.2) |
Imports: | graph, grDevices, graphics, methods, stats, utils, Rgraphviz |
Suggests: | testthat |
Published: | 2017-11-27 |
Author: | Rodrigo Collazo [aut], Pier Taranti [aut, cre] |
Maintainer: | Pier Taranti <ptaranti at gmail.com> |
BugReports: | https://github.com/ptaranti/ceg/issues |
License: | GPL-2 | file LICENSE |
URL: | https://github.com/ptaranti/ceg |
NeedsCompilation: | no |
CRAN checks: | ceg results |
Reference manual: | ceg.pdf |
Package source: | ceg_0.1.0.tar.gz |
Windows binaries: | r-devel: ceg_0.1.0.zip, r-release: ceg_0.1.0.zip, r-oldrel: ceg_0.1.0.zip |
macOS binaries: | r-release: ceg_0.1.0.tgz, r-oldrel: ceg_0.1.0.tgz |
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