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#causality #statistics
As important as the local Markov assumption is, it only gives us information about the independencies in 𝑃 that a DAG implies. It does not even tell us that if 𝑋 and 𝑌 are adjacent in the DAG, then 𝑋 and 𝑌 are dependent. And this additional information is very commonly assumed in causal DAGs. To get this guaranteed dependence between adjacent nodes, we will generally assume a slightly stronger assumption than the local Markov assumption: minimality
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owner: crocodile - (no access) - Introduction_to_Causal_Inference-Nov19_2020-Neal.pdf, p29


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