Anderson, Paul E. and Smith, J. Q. (2005) A graphical framework for representing the semantics of asymmetric models. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2005 (No.12).

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Abstract

Bayesian networks (BNs) are useful for coding conditional independence statements, especially in discrete symmetric models. On
the other hand, event trees (ETs) are convenient for representing asymmetric structure
and how situations unfold. In this paper
we report the development of a new graphical framework called the chain event graph
(CEG). For symmetric models, all conditional independencies in a BN can be expressed through the topology of a CEG. However, unlike the BN, the CEG is equally appropriate for representing conditional independencies in asymmetric systems and does
not need dependent variables to be specified
in advance. As with the BN, it also provides
a framework for learning relevant conditional
probabilities. Furthermore, being a function
of an ET, the CEG is a more
exible way of
representing various causal hypotheses than
the BN. This new framework is illustrated
throughout by a biological regulatory network: the tryptophan metabolic pathway in
the bacterium E. coli.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Statistics -- Graphic methods, Biological control systems -- Mathematical models
Series Name:	Working papers
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
Official Date:	2005
Dates:	Date Event 2005 Published
Volume:	Vol.2005
Number:	No.12
Number of Pages:	7
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC)

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