In terms of narrowing-down-model-space, most of the work (i.e. most of the model-elimination) is in reconstructing the undirected graphical structure; figuring out which direction each arrow goes is relatively easy after that.
This depends a lot on the field, no? If it’s too expensive or unethical to intervene, or one plain and simply doesn’t understand the variables well enough to intervene, then figuring out the direction of the causal arrows can be difficult.
It turns out that model testing in high-dimensional systems is one of the places where the advantage of modern Bayesianism is largest.
Interesting, do you have any additional resources on this?
This depends a lot on the field, no? If it’s too expensive or unethical to intervene, or one plain and simply doesn’t understand the variables well enough to intervene, then figuring out the direction of the causal arrows can be difficult.
Interesting, do you have any additional resources on this?