Mathematics – Statistics Theory
Scientific paper
2010-07-22
Proceedings of the 26th Conference of Uncertainty in Artificial Intelligence (2010)
Mathematics
Statistics Theory
8 pages, 3 figures, companion website: http://graphicalmodels.info
Scientific paper
The long-standing identification problem for causal effects in graphical models has many partial results but lacks a systematic study. We show how computer algebra can be used to either prove that a causal effect can be identified, generically identified, or show that the effect is not generically identifiable. We report on the results of our computations for linear structural equation models, where we determine precisely which causal effects are generically identifiable for all graphs on three and four vertices.
Garcia-Puente Luis David
Spielvogel Sarah
Sullivant Seth
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