Routines for simple graphs and network analysis. It can
handle large graphs very well and provides functions for generating random
and regular graphs, graph visualization, centrality methods and much more.

Network Analysis and Visualization

package-ubuntu-20.04-r-4.0.5#cran#igraph-1.2.10

<p><code>sample_hrg</code> samples a graph from a given hierarchical random graph
model.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>hrg</code></td>
<td>
<p>A hierarchical random graph model.</p>
</td>
</tr></table>

<p>Other hierarchical random graph functions: 
<code><a href="consensus_tree.html">consensus_tree</a>()</code>,
<code><a href="fit_hrg.html">fit_hrg</a>()</code>,
<code><a href="hrg-methods.html">hrg-methods</a></code>,
<code><a href="hrg_tree.html">hrg_tree</a>()</code>,
<code><a href="hrg.html">hrg</a>()</code>,
<code><a href="predict_edges.html">predict_edges</a>()</code>,
<code><a href="print.igraphHRGConsensus.html">print.igraphHRGConsensus</a>()</code>,
<code><a href="print.igraphHRG.html">print.igraphHRG</a>()</code>
</p>

package-ubuntu-20.04-r-4.0.5#cran#igraph-1.2.10#docs#sample_hrg

sample_hrg

Description

Usage

Arguments

Value

See Also

igraph

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