Software

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).


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

Ċ
Mike Salter-Townshend,
Nov 19, 2014, 2:02 AM
ċ
Mike Salter-Townshend,
Nov 19, 2014, 1:58 AM
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