missSBM: Handling missing data in Stochastic Block Models
When a network is partially observed (here, missing dyads, that is, entries with NA in the adjacency matrix rather than 1 or 0), it is possible to account for the underlying process that generates those NAs. missSBM is an R package for adjusting the popular Stochastic Block Models from network data sampled under various missing data conditions.
Please cite our work using the following references:
- T. Tabouy, P. Barbillon, J. Chiquet. Variational Inference for Stochastic Block Models from Sampled Data, 2018 link