# stCEG: An R Package for Modelling Events over Spatial Areas Using Chain Event Graphs

arXiv: https://arxiv.org/abs/2507.06726 · HTML: https://mlsanity.com/paper/2507.06726/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 21 references that are in the map.
- First posted on arXiv 9 Jul 2025.

## Builds on (most cited first, 5 of 5)

- [Context-Specific Independence in Bayesian Networks](https://mlsanity.com/paper/1302.3562/) (2013)
- [The R Package stagedtrees for Structural Learning of Stratified Staged Trees](https://mlsanity.com/paper/2004.06459/) (2020)
- [Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models](https://mlsanity.com/paper/1310.1187/) (2013)
- [cegpy: Modelling with Chain Event Graphs in Python](https://mlsanity.com/paper/2211.11366/) (2022)
- [An N Time-Slice Dynamic Chain Event Graph](https://mlsanity.com/paper/1808.05726/) (2018)

## Abstract (arXiv)

stCEG is an R package which allows a user to fully specify a Chain Event Graph (CEG) model from data and to produce interactive plots. It includes functions for the user to visualise spatial variables they wish to include in the model. There is also a web-based graphical user interface (GUI) provided, increasing ease of use for those without knowledge of R. We demonstrate stCEG using a dataset of homicides in London, which is included in the package. stCEG is the first software package for CEGs that allows for full model customisation.