1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2022★ 1 cited
cegpy: Modelling with Chain Event Graphs in Python
Gareth Walley, Aditi Shenvi, Peter Strong +1
Chain event graphs (CEGs) are a recent family of probabilistic graphical models that generalise the popular Bayesian networks (BNs) family. Crucially, unlike BNs, a CEG is able to…
stat.ME2022
Scalable Model Selection for Staged Trees: Mean-posterior Clustering and Binary Trees
Peter Strong, Jim Q. Smith
Several structure-learning algorithms for staged trees, asymmetric extensions of Bayesian networks, have been proposed. However, these either do not scale efficiently as the number…
stat.AP2021
A Bayesian Analysis of Migration Pathways using Chain Event Graphs of Agent Based Models
Peter Strong, Alys McAlpine, Jim Q Smith
Agent-Based Models (ABMs) are often used to model migration and are increasingly used to simulate individual migrant decision-making and unfolding events through a sequence of heur…