Constructing a Chain Event Graph from a Staged Tree

by   Aditi Shenvi, et al.
University of Warwick

Chain Event Graphs (CEGs) are a recent family of probabilistic graphical models - a generalisation of Bayesian Networks - providing an explicit representation of structural zeros and context-specific conditional independences within their graph topology. A CEG is constructed from an event tree through a sequence of transformations beginning with the colouring of the vertices of the event tree to identify one-step transition symmetries. This coloured event tree, also known as a staged tree, is the output of the learning algorithms used for this family. Surprisingly, no general algorithm has yet been devised that automatically transforms any staged tree into a CEG representation. In this paper we provide a simple iterative backward algorithm for this transformation. Additionally, we show that no information is lost from transforming a staged tree into a CEG. Finally, we demonstrate that with an optimal stopping time, our algorithm is more efficient than the generalisation of a special case presented in Silander and Leong (2013). We also provide Python code using this algorithm to obtain a CEG from any staged tree along with the functionality to add edges with sampling zeros.


page 1

page 2

page 3

page 4


Beyond Conjugacy for Chain Event Graph Model Selection

Chain event graphs are a family of probabilistic graphical models that g...

cegpy: Modelling with Chain Event Graphs in Python

Chain event graphs (CEGs) are a recent family of probabilistic graphical...

Propagation for Dynamic Continuous Time Chain Event Graphs

Chain Event Graphs (CEGs) are a family of event-based graphical models t...

Propagation using Chain Event Graphs

A Chain Event Graph (CEG) is a graphial model which designed to embody c...

Properties of an N Time-Slice Dynamic Chain Event Graph

A Dynamic Chain Event Graph (DCEG) provides a rich tree-based framework ...

An N Time-Slice Dynamic Chain Event Graph

The Dynamic Chain Event Graph (DCEG) is able to depict many classes of d...

Bayesian Diagnostics for Chain Event Graphs

Chain event graphs have been established as a practical Bayesian graphic...

Please sign up or login with your details

Forgot password? Click here to reset