Barclay, LM, Collazo, RA, Smith, JQ et al. (2 more authors) (2015) The Dynamic Chain Event Graph. Electronic Journal of Statistics, 9 (2). pp. 2130-2169. ISSN 1935-7524
Abstract
In this paper we develop a formal dynamic version of Chain Event Graphs (CEGs), a particularly expressive family of discrete graph-
ical models. We demonstrate how this class links to semi-Markov models and provides a convenient generalization of the Dynamic Bayesian Network (DBN). In particular we develop a repeating time-slice Dynamic CEG providing a useful and simpler model in this family. We demonstrate how the Dynamic CEG’s graphical formulation exhibits asymmetric conditional independence statements and also how each model can be estimated in a closed form enabling fast model search over the class. The expressive power of this model class together with its estimation is illustrated throughout by a variety of examples that include the risk of childhood hospitalization and the efficacy of a flu vaccine.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 The Authors. This is an open access article under the terms of the Creative Commons Attribution License CC-BY. |
Keywords: | Chain Event Graphs; Markov Processes; Probabilistic Graphical Models; Dynamic Bayesian Networks |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Oct 2015 14:16 |
Last Modified: | 11 Feb 2022 16:57 |
Published Version: | http://dx.doi.org/10.1214/15-EJS1068 |
Status: | Published |
Publisher: | Institute of Mathematical Statistics |
Identification Number: | 10.1214/15-EJS1068 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:90184 |