__VBLPCM: Variational Bayesian inference for the Latent Position Cluster Model for networks__

### This package is now available through the
CRAN R repository and can be installed using install.packages("VBLPCM") in R

A faster approximate alternative to using latentnet. Interfaces C code to fit a
Variational Bayes approximation to the posterior for the Latent Position Cluster Model for networks.

This package is designed to be used as an alternative to the latentnet package when network
size computationally prohibits latentnet. It uses a Variational Bayesian Expectation Maximisation algorithm
to compute a closed-form approximation to the posterior that the ergmm function in latentnet samples
from. It may be thought of as an intermediary approximation that is more accurate than
the two-stage MLE fit provided by latentnet but a faster approximation to the MCMC sampler provided
by latentnet. In fact, the VB iterations also converge quicker than the two-stage MLE.

Furthermore, VBLPCM takes advantage of the stratified sampler of Adrian Raftery, Xiaoyue Niu, Peter
Hoff and Ka Yee Yeung. This approximation to the (log)likelihood allows for even larger networks to
be analysed (see tech report).

This model fits facebook networks nicely. To fit the model to your network use these steps:

(You'll need to have libxml2-dev installed before you install igraph for it to handle graphml files.)

1. Download your facebook network using

Bernie Hogan's app.
Choose the GraphML option.

2. In R:

library(igraph)
### load the network using igraph
g<-read.graph("path_to_downloaded_graphml_file",format="graphml")
### Convert to a network:
net<-network(get.adjacency(g,sparse=FALSE),directed=FALSE)
### Add in the names
network.vertex.names(net)<-igraph::get.vertex.attribute(g,"id")
detach("package:igraph")
### Fit the model to the network, choosing G and d
v.fit<-vblpcmfit(vblpcmstart(net,G=G,d=d))
### Plot it
plot(v.fit)
### Show the point estimates of the groups
vblpcmgroups(v.fit)

## Working Binaries

Here are the binaries for Linux and windows for upcoming versions of VBLPCM.

VBLPCM_2.4.3.tar.gz (Unix / Linux)

VBLPCM_2.4.3.zip (Windows)

__Review of Statistical Network Analysis: Models, Algorithms and Software__

### About

We provide the R scripts used to run the examples in the

supplementary document
to the paper "Review of Statistical Network Analysis: Models, Algorithms and Software" (Statistical Analysis and Data Mining, 2012).

The entire directory (input files and R scripts) is archived in

supplement.zip

### R files

SummaryStats.R

block.R

hclust.R

blockmodel.R

GirvanNewman.R

Spectral.R

p1_fast.R

p1_ergm.R

p2_lawyers.R

p2.R

ergm.R

lpcm.R

MMSB.R

roc.R