Matlab package BNPgraph

Matlab package: BNPgraph
Sparse graphs using exchangeable random measures

Description

This Matlab package implements algorithms for simulation and posterior inference with the class of sparse graph models introduced by Caron and Fox (2014). It allows to simulate graphs with a given level of sparsity,to infer the parameters of observed networks (sociability parameters associated to nodes) and to assess the sparsity of a given network.

The package has been tested on Matlab R2014a and requires the statistics toolbox.

F. Caron, E.B. Fox. Sparse graphs using exchangeable random measures. arXiv:1401.1137. Download paper.

Installation

Download the zip file
Unzip it in some folder
Run the test file test.m

In order to use the package, the folders "GGP" and "utils" need to be added to the Matlab path, using the command addpath (see the test file).

Contents

Test script

test.m

Demos of the package

demo_graph.m: simulates a GGP graph and runs a MCMC algorithm for posterior inference on that graph [html version]
demo_bipgraph.m: simulates a GGP bipartite graph and runs a MCMC algorithm for posterior inference on that graph [html version]
demo_sparse.m: simulates graphs from various models and different sizes to empirically show their sparsity properties [html version]
demo_degree.m: simulates GGP graphs with different values of the parameter sigma and shows the associated empirical degree distributions[ html version]
demo_experiments.m: performs posterior inference on the yeast protein interaction network [html version]

Main functions: simulation and posterior inference on graphs

graphmodel: creates a graph model object
graphrnd: samples a graph
graphmcmc: creates a MCMC object
graphmcmcsamples: runs a MCMC algorithm for posterior inference on graphs

Other samplers of interest:

GGPrnd: samples from a generalized gamma process
GGPsumrnd: samples from the distribution of the sum of the weights in a generalized gamma process
etstablernd: samples from an exponentially tilted stable distribution

Latest corrections

Last update: 01-05-2015. First version of the package.

(C) Copyright 2015 François Caron,University of Oxford

caron@stats.ox.ac.uk
http://www.stats.ox.ac.uk/~caron/

Permission is granted for anyone to copy, use, or modify these programs and accompanying documents for purposes of research or education, provided this copyright notice is retained, and note is made of any changes that have been made.

These programs and documents are distributed without any warranty, express or implied.
As the programs were written for research purposes only, they have not been tested to the degree that would be advisable in any important application.
All use of these programs is entirely at the user's own risk.