Variational Bayes Latent Position Cluster Model for Networks

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Documentation for package ‘VBLPCM’ version 2.4.9

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VBLPCM-package VBLPCM: Variational Bayes for the Latent Position Cluster Model for networks
aids aids blogs data as a "network" object
aids.net aids blogs data as a "network" object
E_to_Y create an adjacency matrix from an edgelist.
fruchterman_reingold Perform Fruchterman-Reingold layout of a network in 2 or more dimensions.
gof.vblpcm Goodness of fit based on simulations from the fitted object.
hops_to_hopslist create a handy matrix of vectors to store the hopslist
log_like_forces create an initial configuration for the latent positions.
plot.vblpcm plot the posterior latent positions and groupings and network
predict.vblpcm Find all link probabilities
print.vblpcm print the fitted vblpcm object
samplike Cumulative network of positive affection within a monastery as a "network" object
sampson Cumulative network of positive affection within a monastery as a "network" object
summary.vblpcm summary of a fitted vblpcm object.
VBLPCM VBLPCM: Variational Bayes for the Latent Position Cluster Model for networks
vblpcmbic calculate the BIC for the fitted VBLPCM object
vblpcmcovs create the design matrix for the network analysis
vblpcmdrawpie add a piechart of group memberships of a node to a network plot; taken mainly from latentnet equivalent
vblpcmfit fit the variational model through EM type iterations
vblpcmgroups list the maximum VB a-posteriori group memberships.
vblpcmKL print and returns the Kullback-Leibler divergence from the fitted vblpcm object to the true LPCM posterior
vblpcmroc ROC curve plot for vblpcmfit
vblpcmstart Generate sensible starting configuration for the variational parameter set.
Y simulated.network
Y_to_E calculate the edgelist for a given adjacency matrix
Y_to_M calculate the missing edges as an edgelist from an adjacency matrix with NaNs indicating missing links
Y_to_nonE calculate a non-edge list from an adjacency matrix