compute BIC score when fitting a DCSBM to network data
eval_dcsbm_bic(A, z, K, poi)BIC score
adjacency matrix
label vector
number of community in z
whether to use Poisson version of likelihood
the BIC score is calculated by -2*log likelihood minus \(K\times(K + 1)\times log(n)\)
BIC score is originally proposed in Likelihood-based model selection for stochastic block models Wang, YX Rachel, Peter J. Bickel, The Annals of Statistics 45, no. 2 (2017): 500-528.
The details of modified implementation can be found in Adjusted chi-square test for degree-corrected block models, Linfan Zhang, Arash A. Amini, arXiv preprint arXiv:2012.15047, 2020.
eval_dcsbm_like, eval_dcsbm_loglr