Uses the half-trek criterion of Foygel, Draisma, and Drton (2012) determine
which edges in a mixed graph are generically identifiable. Depending on your
application it faster to use the
instead of this one, this function has the advantage of returning additional
TRUE or FALSE determining whether or not the Tian decomposition should be used before running the current generic identification algorithm. In general letting this be TRUE will make the algorithm faster and more powerful.
see the return value of
Foygel, R., Draisma, J., and Drton, M. (2012) Half-trek criterion for generic identifiability of linear structural equation models. Ann. Statist. 40(3): 1682-1713.
Jin Tian. 2005. Identifying direct causal effects in linear models. In Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (AAAI'05), Anthony Cohn (Ed.), Vol. 1. AAAI Press 346-352.
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