NetMix (0.1.4)

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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 .

Maintainer: Santiago Olivella
Author(s): Kosuke Imai [aut, cre], Tyler Pratt [aut, cre], Adeline Lo [aut, cre], Santiago Olivella [aut, cre]

License: GPL (>= 2)

Uses: clue, gtools, igraph, lda, Matrix, Rcpp, RSpectra, doParallel, ergm, foreach, ggplot2, network

Released 5 months ago.



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