Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
418756 | Discrete Applied Mathematics | 2009 | 19 Pages |
Abstract
I study the interplay between stochastic dependence and causal relations within the setting of Bayesian networks and in terms of information theory. The application of a recently defined causal information flow measure provides a quantitative refinement of Reichenbach’s common cause principle.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Nihat Ay,