Variational Bayes Latent Position Cluster Model for Networks
create an adjacency matrix from an edgelist.
Perform Fruchterman-Reingold layout of a network in 2 or more dimensio...
Goodness of fit based on simulations from the fitted object.
create a handy matrix of vectors to store the hopslist
create an initial configuration for the latent positions.
plot the posterior latent positions and groupings and network
Find all link probabilities
print the fitted vblpcm object
summary of a fitted vblpcm object.
Internal VBLPCM objects
VBLPCM: Variational Bayes for the Latent Position Cluster Model for ne...
calculate the BIC for the fitted VBLPCM object
create the design matrix for the network analysis
add a piechart of group memberships of a node to a network plot; taken...
fit the variational model through EM type iterations
list the maximum VB a-posteriori group memberships.
print and returns the Kullback-Leibler divergence from the fitted vblp...
ROC curve plot for vblpcmfit
Generate sensible starting configuration for the variational parameter...
calculate the edgelist for a given adjacency matrix
calculate the missing edges as an edgelist from an adjacency matrix wi...
calculate a non-edge list from an adjacency matrix
Fit and simulate latent position and cluster models for network data, using a fast Variational Bayes approximation developed in Salter-Townshend and Murphy (2013) <doi:10.1016/j.csda.2012.08.004>.