The Random Subgraph Model

Description

Partition the vertices of a directed network with typed edges into clusters describing the connection patterns of subgraphs given as inputs. The inference is performed using a variational Bayes EM algorithm and the estimation of the number of clusters is obtained through a variational approximation of the marginal log likelihood.

Details

Author(s)

Yacine Jernite, Laetitia Nouedoui, Charles Bouveyron, Pierre Latouche. Maintainer: Who to complain to <yourfault@somewhere.net>

References

Yacine Jernite, Pierre Latouche, Charles Bouveyron, Patrick Rivera, Laurent Jegou and Stephane Lamasse(2012), The Random Subgraph Model for the Analysis of an Ecclesiastical Network in Merovingian Gaul, http://arxiv.org/abs/1212.5497

See Also

rsm, summary.rsm, plot.rsm

Examples

data(Regions)
res <- rsm(Regions$X, Regions$sub, Klist=2:4, nbredo=1, maxit=5) 
plot(res)
## summary(res)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(Rambo)
Loading required package: sna
sna: Tools for Social Network Analysis
Version 2.3-2 created on 2014-01-13.
copyright (c) 2005, Carter T. Butts, University of California-Irvine
 For citation information, type citation("sna").
 Type help(package="sna") to get started.

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Rambo/Rambo-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Rambo-package
> ### Title: The Random Subgraph Model
> ### Aliases: Rambo-package Rambo RAMBO
> ### Keywords: rsm
> 
> ### ** Examples
> 
> data(Regions)
> res <- rsm(Regions$X, Regions$sub, Klist=2:4, nbredo=1, maxit=5) 
> plot(res)
> ## summary(res)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>