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Causal discovery through MAP selection of stratified chain event graphs
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Cowell, Robert G. and Smith, J. Q. (2014) Causal discovery through MAP selection of stratified chain event graphs. Electronic Journal of Statistics, Volume 8 (Number 1). pp. 965-997. doi:10.1214/14-EJS917 ISSN 1935-7524.
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Official URL: http://dx.doi.org/10.1214/14-EJS917
Abstract
We introduce a subclass of chain event graphs that we call stratified chain event graphs, and present a dynamic programming algorithm for the optimal selection of such chain event graphs that maximizes a decomposable score derived from a complete independent sample. We apply the algorithm to such a dataset, with a view to deducing the causal structure of the variables under the hypothesis that there are no unobserved confounders. We show that the algorithm is suitable for small problems. Similarities with and differences to a dynamic programming algorithm for MAP learning of Bayesian networks are highlighted, as are the relations to causal discovery using Bayesian networks.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | Electronic Journal of Statistics | ||||
Publisher: | Institute of Mathematical Statistics | ||||
ISSN: | 1935-7524 | ||||
Official Date: | 2014 | ||||
Dates: |
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Volume: | Volume 8 | ||||
Number: | Number 1 | ||||
Page Range: | pp. 965-997 | ||||
DOI: | 10.1214/14-EJS917 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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