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The causal manipulation and Bayesian estimation of chain event graphs
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Riccomagno, Eva and Smith, J. Q. (2005) The causal manipulation and Bayesian estimation of chain event graphs. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2005 (No.16).
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Official URL: http://www2.warwick.ac.uk/fac/sci/statistics/crism...
Abstract
Discrete Bayesian Networks (BNs) have been very successful as
a framework both for inference and for expressing certain causal hypotheses. In this paper we present a class of graphical models called
the chain event graph (CEG) models, that generalises the class of discrete BN models. This class is suited for representing conditional independence and sample space structures of asymmetric models. It retains many useful properties of discrete BNs, in particular admitting
conjugate estimation. It provides a flexible and expressive framework
for representing and analysing the implications of causal hypotheses,
expressed in terms of the effects of a manipulation of the generating
underlying system.We prove that, as for a BN, identifiability analyses
of causal effects can be performed through examining the topology
of the CEG graph, leading to theorems analogous to the Backdoor
theorem for the BN.
Item Type: | Working or Discussion Paper (Working Paper) | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Library of Congress Subject Headings (LCSH): | Graphical modeling (Statistics), Bayesian statistical decision theory | ||||
Series Name: | Working papers | ||||
Publisher: | University of Warwick. Centre for Research in Statistical Methodology | ||||
Place of Publication: | Coventry | ||||
Official Date: | 2005 | ||||
Dates: |
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Volume: | Vol.2005 | ||||
Number: | No.16 | ||||
Number of Pages: | 36 | ||||
Status: | Not Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Date of first compliant deposit: | 1 August 2016 | ||||
Date of first compliant Open Access: | 1 August 2016 |
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