Package: NetMix 0.2.0.2
NetMix: Dynamic Mixed-Membership Network Regression Model
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>.
Authors:
NetMix_0.2.0.2.tar.gz
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NetMix.pdf |NetMix.html✨
NetMix/json (API)
NEWS
# Install 'NetMix' in R: |
install.packages('NetMix', repos = c('https://solivella.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/solivella/netmix/issues
- lazega_dyadic - Dyadic predictors in the Lazega friendship network (Lazega 2001).
- lazega_monadic - Monadic predictors in the Lazega friendship network (Lazega 2001).
Last updated 12 months agofrom:627b94ab50. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 24 2024 |
R-4.5-win-x86_64 | OK | Oct 24 2024 |
R-4.5-linux-x86_64 | OK | Oct 24 2024 |
R-4.4-win-x86_64 | OK | Oct 24 2024 |
R-4.4-mac-x86_64 | OK | Oct 24 2024 |
R-4.4-mac-aarch64 | OK | Oct 24 2024 |
R-4.3-win-x86_64 | OK | Oct 24 2024 |
R-4.3-mac-x86_64 | OK | Oct 24 2024 |
R-4.3-mac-aarch64 | OK | Oct 24 2024 |
Exports:alphaGradalphaLBoundapproxBcoef.mmsbmcovFXgetZgofgof.mmsbmhead.mmsbmmmsbmmmsbm_fitplot.mmsbmpredict.mmsbmsimulate.mmsbmsummary.mmsbmvcov.mmsbm
Dependencies:cliclueclustercpp11gluegtoolsigraphlatticeldalifecyclemagrittrMASSMatrixpkgconfigpoisbinomRcppRcppArmadillorlangvctrs