Causal Markov condition

The Causal Markov (CM) condition states that, conditional on the set of all its direct causes, a node is independent of all variables which are not effects or direct causes of that node. In the event that the structure of a Bayesian network accurately depicts causality, the two conditions are equivalent.

Causal Markov condition - Wikipedia Jump to content From Wikipedia, the free encyclopedia The Causal Markov (CM) condition states that, conditional on the set of all its direct causes, a node is independent of all variables which are not effects or direct causes of that node. [ 1 ] In the event that the structure of a Bayesian network accurately depicts causality , the two conditions are equivalent. This is related to the Markov condition , an assumption made in Bayesian probability theory , that every node in a Bayesian network is conditionally independent of its nondescendants, given its par

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