metagraph

Plot the metagraph of the parameter of the stochastic block model associated
with one of the estimated graph clusters

Graph clustering using an agglomerative algorithm to maximize the
integrated classification likelihood criterion and a mixture of stochastic
block models. The method is described in the article "Model-based clustering
of multiple networks with a hierarchical algorithm" by
T. Rebafka (2022) <arXiv:2211.02314>.

Tabea Rebafka

graphclust

Hierarchical Graph Clustering for a Collection of Networks

metagraph function

<dl><dt>nb</dt>
<dd>number of the cluster we are interested in</dd>
<dt>res</dt>
<dd>output of graphClustering()</dd>
<dt>title</dt>
<dd>title of the figure</dd>
<dt>edge.width.cst</dt>
<dd>width of edges in the metagraph</dd></dl>

Arguments

Plot the metagraph of the parameter of the stochastic block model associated
with one of the estimated graph clusters — metagraph

<dl>

<dt>nb</dt>
<dd>number of the cluster we are interested in</dd>


<dt>res</dt>
<dd>output of graphClustering()</dd>


<dt>title</dt>
<dd>title of the figure</dd>


<dt>edge.width.cst</dt>
<dd>width of edges in the metagraph</dd>

</dl>

metagraph: Plot the metagraph of the parameter of the stochastic block model associated with one of the estimated graph clusters

Description

Usage

Value

Arguments

Examples