Goodness of Causal Fit

We propose a Goodness of Causal Fit (GCF) measure which depends on Judea Pearl's ``do" interventions. This is different from Goodness of Fit (GF) measures, which do not use interventions. Given a set cal G of DAGs with the same nodes, to find a good G∈ cal G, we propose plotting GCF(G) versus GF(G) for all G∈ cal G, and finding a graph G∈ cal G with a large amount of both types of goodness.