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NetMix

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.

Installation

To install the latest CRAN version, copy and paste the following in a running R console: install.packages("NetMix").

For the latest development version, copy and paste the following (assuming you have the remotes package installed): remotes::install_github("solivella/NetMix")

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Version

Install

install.packages('NetMix')

Monthly Downloads

274

Version

0.1.5

License

GPL (>= 2)

Maintainer

Santiago Olivella

Last Published

January 14th, 2020

Functions in NetMix (0.1.5)

approxB

Internal functions and generics for mmsbm package
head.mmsbm

Identify nodes with most frequent membership in latent groups
lazega_monadic

Monadic predictors in the Lazega friendship network (Lazega 2001).
gof

Posterior predictive checks using structural network charactericts
mmsbm_fit

Fitter Function for dynamic MMSBM Model
mmsbm

Dynamic mixed-membership stochastic blockmodel with covariates
lazega_dyadic

Dyadic predictors in the Lazega friendship network (Lazega 2001).
coef.mmsbm

Extract Regression Coefficients for a Fitted mmsbm Object
NetMix-package

NetMix
covFX

Generate estimated monadic covariate effects for estimated mmsbm model
plot.mmsbm

Various visualization tools for 'mmsbm' objects
vcov.mmsbm

Extract Variance-Covariance Matrix for a Fitted mmsbm Object
predict.mmsbm

Predict edges based on estimated mmsbm model
simulate.mmsbm

Simulate a complete sociomatrix from an mmsbm object
summary.mmsbm

Summarize 'mmsbm' object