Uncertainty in Artificial Intelligence
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Directed Cyclic Graphical Representations of Feedback Models
Peter Spirtes
Abstract:
The use of directed acyclic graphs (DAGs) to represent conditional independence relations among random variables has proved fruitful in a variety of ways. Recursive structural equation models are one kind of DAG model. However, non-recursive structural equation models of the kinds used to model economic processes are naturally represented by directed cyclic graphs with independent errors, a characterization of conditional independence errors, a characterization of conditional independence constraints is obtained, and it is shown that the result generalizes in a natural way to systems in which the error variables or noises are statistically dependent. For non-linear systems with independent errors a sufficient condition for conditional independence of variables in associated distributions is obtained.
Keywords:
Pages: 491-498
PS Link:
PDF Link: /papers/95/p491-spirtes.pdf
BibTex:
@INPROCEEDINGS{Spirtes95,
AUTHOR = "Peter Spirtes ",
TITLE = "Directed Cyclic Graphical Representations of Feedback Models",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "491--498"
}


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