This functions computes functional constraints known as Verma constraints for a joint distribution of a given semi-Markovian causal model.
A list of lists, each with five components corresponding to the functional constraint. The two equal c-factors that imply the functional independence are described by
rhs.cfactor and their expressions are given by
rhs.expr respectively. The independent variables are given by
Tian, J., Pearl J. 2002 On Testable Implications of Causal Models with Hidden variables. Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence, 519–527.
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