Dynamic Mixed-Membership Network Regression Model R package NetMix version 0.2.0.3 Stochastic collapsed variational inference on 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 <https://www.santiagoolivella.info/pdfs/socnet.pdf>. Software Depends: R (>= 4.1.0) Imports: clue (>= 0.3-58), graphics (>= 3.5.2), grDevices (>= 3.5.2), gtools (>= 3.8.1), igraph (>= 1.2.4.1), 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), 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) Santiago Olivella <olivella@unc.edu> Comprehensive R Archive Network (CRAN) Santiago Olivella [aut, cre], Adeline Lo [aut], Tyler Pratt [aut], Kosuke Imai [ctb] GPL (>= 2) 2025-06-05 application/tgz https://CRAN.R-project.org/package=NetMix doi:10.32614/CRAN.package.NetMix