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 < http://santiagoolivella.info/wp-content/uploads/2018/07/dSBM_Reg.pdf>.


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install.packages("NetMix")

0.1.4 by Santiago Olivella, 4 months ago


Report a bug at https://github.com/solivella/NetMix/issues


Browse source code at https://github.com/cran/NetMix


Authors: Kosuke Imai [aut, cre] , Tyler Pratt [aut, cre] , Adeline Lo [aut, cre] , Santiago Olivella [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports clue, graphics, grDevices, gtools, igraph, lda, Matrix, methods, Rcpp, RSpectra, stats, utils

Suggests doParallel, ergm, foreach, ggplot2, network

Linking to Rcpp

System requirements: C++11


See at CRAN