R: Fit the Mixture of Experts Latent Position Cluster Model to Network Data

# Fit the Mixture of Experts Latent Position Cluster Model to Network Data

## Documentation for package ‘MEclustnet’ version 1.2.2

- DESCRIPTION file
- Package NEWS

## Help Pages

MEclustnet-package | MEclustnet: A package for model-based clustering of nodes in a network, accounting for covariates.
calclambda | Title Compute mixing proportions
calcloglikelihood | Calculate the log likelihood function of the data.
calcm | Totals the number of observations in each cluster.
calcpis | Calculate link probabilities.
formatting.covars | Reformat matrix of covariates.
invariant | Account for invariance of configurations.
labelswitch | Label switching correction.
lawyers.adjacency.advice | Adjacency matrix detailing the presence or absence of advice links between the 'Lazega Lawyers'.
lawyers.adjacency.coworkers | Adjacency matrix detailing the presence or absence of coworker links between the 'Lazega Lawyers'.
lawyers.adjacency.friends | Adjacency matrix detailing the presence or absence of friendship links between the 'Lazega Lawyers'.
lawyers.covariates | A matrix of covariates of the 'Lazega Lawyers'.
MEclustnet | MEclustnet: A package for model-based clustering of nodes in a network, accounting for covariates.
plotMEclustnet | Plot latent position network.
summaryMEclustnet | Summary of MEclustnet object.
updatebeta | Update the logistic regression parameters in the link probabilities model.
updateK | Update the cluster membership vector.
updatemu | Update the mean of each cluster.
updatesigma2 | Update variances in each cluster.
updatetau | Update the logistic regression parameters in the mixing proportions model.
updatez | Update step for the latent locations.
us.twitter.adjacency | Directed adjacency matrix detailing the presence or absence of Twitter friend/follower links between US politicians.
us.twitter.covariates | A matrix of covariates of the US politicians.