On 12.09.2017 13:01, Philipp-Maximilian Jacob wrote: > Hi Tiago, > > Thank you for that explanation. A quick follow-up: > > If calculating likelihoods of both missing and spurious edges would I expect > the output to be on a continuous scale of existence likelihood? Assume there > is an edge “c” which I am assuming to be a missing edge and I calculate the > likelihood ratios by summing across all three edges (based on > `s.get_edges_prob([],[a], entropy_args=dict(partition_dl=False))`, > `s.get_edges_prob([],[b], entropy_args=dict(partition_dl=False))` and > `s.get_edges_prob([c],[], entropy_args=dict(partition_dl=False))`). If I find > \lambda_a > \lambda_c > \lambda_b can I read this that “a” is more likely to > be spurious than “c” is to be missing (which in turn is more likely to be > spurious than "b" is to be missing)? Or is such a comparison not really > meaningful anyways?
Yes, this is totally fine. The "spurious" and "missing" edges are arbitrary modifications to the graph, and the probabilistic model does not distinguish between them. Best, Tiago -- Tiago de Paula Peixoto <[email protected]>
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