Estimates exponentialfamily random graph models for multilevel network data, assuming the multilevel structure is observed. The scope, at present, covers multilevel models where the set of nodes is nested within known blocks. The estimation method uses MonteCarlo maximum likelihood estimation (MCMLE) methods to estimate a variety of canonical or curved exponential family models for binary random graphs. MCMLE methods for curved exponentialfamily random graph models can be found in Hunter and Handcock (2006) <DOI: 10.1198/106186006X133069>. The package supports parallel computing, and provides methods for assessing goodnessoffit of models and visualization of networks.
Package details 


Author  Jonathan Stewart [cre, aut], Michael Schweinberger [ctb] 
Maintainer  Jonathan Stewart <[email protected]> 
License  GPL3 
Version  0.5 
Package repository  View on CRAN 
Installation 
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