NetMix: Dynamic Mixed-Membership Network Regression Model

Variational EM estimation of mixed-membership stochastic blockmodel for networks, incorporating node-level predictors of mixed-membership vectors, as well as dyad-level predictors. For networks observed over time, the model defines a hidden Markov process that allows the effects of node-level predictors to evolve in discrete, historical periods. In addition, the package offers a variety of utilities for exploring results of estimation, including tools for conducting posterior predictive checks of goodness-of-fit and several plotting functions. The package implements methods described in Olivella, Pratt and Imai (2019) “Dynamic Stochastic Blockmodel Regression for Social Networks: Application to International Conflicts”, available at <>.

Version: 0.1.5
Depends: R (≥ 3.5.0)
Imports: clue (≥ 0.3-54), graphics (≥ 3.5.2), grDevices (≥ 3.5.2), gtools (≥ 3.8.1), igraph (≥, lda (≥ 1.4.2), Matrix (≥ 1.2-15), MASS (≥ 7.3-51.4), methods (≥ 3.5.2), poisbinom (≥ 1.0.1), Rcpp (≥ 1.0.2), RSpectra (≥ 0.14-0), stats (≥ 3.5.2), utils (≥ 3.5.2)
LinkingTo: Rcpp, RcppArmadillo
Suggests: ergm (≥ 3.9.4), ggplot2 (≥ 3.1.1), network (≥ 1.13), scales (≥ 1.0.0)
Published: 2020-01-14
Author: Santiago Olivella [aut, cre], Adeline Lo [aut, cre], Tyler Pratt [aut, cre], Kosuke Imai [aut, cre]
Maintainer: Santiago Olivella <olivella at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README NEWS
CRAN checks: NetMix results


Reference manual: NetMix.pdf
Package source: NetMix_0.1.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: NetMix_0.1.5.tgz, r-oldrel: NetMix_0.1.5.tgz
Old sources: NetMix archive


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