Package: ceg 0.1.0

ceg: Chain Event Graph

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>.

Authors:Rodrigo Collazo [aut], Pier Taranti [aut, cre]

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Peer review:

Bug tracker:https://github.com/ptaranti/ceg/issues

On CRAN:

7 exports 2 stars 0.83 score 3 dependencies 1 scripts 174 downloads

Last updated 6 years agofrom:026c1a1141. Checks:OK: 7. Indexed: yes.

Exports:CategoryCheckAndCleanDataplotStratified.ceg.modelStratified.event.treeStratified.staged.treeVariable

Dependencies:BiocGenericsgraphRgraphviz