state = gt.minimize_blockmodel_dl(g, deg_corr=False, layers=True,
state_args=dict(ec=g.ep.value, layers=False))
I'm trying to make sure I understand the LayeredBlockState correctly. Are the following statements correct?
- The independent layers version is used, which means that there is one layer for every possible number of co-appearances. This means that number of co-appearances is treated as a categorical, rather than an ordinal variable.
- If one wanted to encourage the model to assort actors into the same block if they have many co-appearances, the following fit would be more appropriate:
state = gt.minimize_blockmodel_dl(g, deg_corr=False, layers=False,
state_args=dict(eweight=g.ep.value))
(If I'm right, then I find that the second model is closer to what an applied scientist would be interested in...)
Many thanks for clearing this up,
Peter