cluster

cluster_hierarchical

cluster_concor

Methods for equivalence clustering

A set of tools for analysing multimodal networks.
All functions operate with matrices, edge lists,
and 'igraph', 'network', and 'tidygraph' objects,
and on one-mode, two-mode (bipartite), and sometimes three-mode networks.
It includes functions for measuring
centrality, centralization, cohesion, closure, and constraint,
as well as for network block-modelling and regression.
The package is released as a complement to
'Multimodal Political Networks' (2021, ISBN:9781108985000),
and includes various datasets used in the book in addition to other network data.

James Hollway

migraph

Tools for Multimodal Network Analysis

Jael Tan

Bernhard Bieri

Henrique Sposito

cluster function

<dl><dt>census</dt>
<dd>A matrix returned by a <code>node_*_census()</code> function.</dd>
<dt>distance</dt>
<dd>Character string indicating which distance metric
to pass on to <code><a href="/link/stats%3A%3Adist?package=migraph&version=0.10.6" data-mini-rdoc="migraph::stats::dist">stats::dist</a></code>.
By default <code>"euclidean"</code>, but other options include
<code>"maximum"</code>, <code>"manhattan"</code>, <code>"canberra"</code>, <code>"binary"</code>, and <code>"minkowski"</code>.
Fewer, identifiable letters, e.g. <code>"e"</code> for Euclidean, is sufficient.</dd>
<dt>object</dt>
<dd>An object of a migraph-consistent class:<ul>
<li>matrix (adjacency or incidence) from <code>{base}</code> R</li>
<li>edgelist, a data frame from <code>{base}</code> R or tibble from <code>{tibble}</code></li>
<li>igraph, from the <code>{igraph}</code> package</li>
<li>network, from the <code>{network}</code> package</li>
<li>tbl_graph, from the <code>{tidygraph}</code> package</li>
</ul></dd></dl>

Arguments

<ul>
<li><code>cluster_hierarchical</code>: Returns a hierarchical clustering object
created by <code><a href="/link/stats%3A%3Ahclust()?package=migraph&version=0.10.6" data-mini-rdoc="migraph::stats::hclust()">stats::hclust()</a></code></li>
<li><code>cluster_concor</code>: Returns a hierarchical clustering object
created from a convergence of correlations procedure (CONCOR)</li>
</ul>

Functions

Methods for equivalence clustering — cluster

<dl>

<dt>census</dt>
<dd>A matrix returned by a <code>node_*_census()</code> function.</dd>


<dt>distance</dt>
<dd>Character string indicating which distance metric
to pass on to <code><a href='https://rdrr.io/r/stats/dist.html'>stats::dist</a></code>.
By default <code>"euclidean"</code>, but other options include
<code>"maximum"</code>, <code>"manhattan"</code>, <code>"canberra"</code>, <code>"binary"</code>, and <code>"minkowski"</code>.
Fewer, identifiable letters, e.g. <code>"e"</code> for Euclidean, is sufficient.</dd>


<dt>object</dt>
<dd>An object of a migraph-consistent class:<ul>
<li>matrix (adjacency or incidence) from <code>{base}</code> R</li>
<li>edgelist, a data frame from <code>{base}</code> R or tibble from <code>{tibble}</code></li>
<li>igraph, from the <code>{igraph}</code> package</li>
<li>network, from the <code>{network}</code> package</li>
<li>tbl_graph, from the <code>{tidygraph}</code> package</li>
</ul></dd>

</dl>

<ul>
<li><code>cluster_hierarchical</code>: Returns a hierarchical clustering object
created by <code><a href='https://rdrr.io/r/stats/hclust.html'>stats::hclust()</a></code></li>
<li><code>cluster_concor</code>: Returns a hierarchical clustering object
created from a convergence of correlations procedure (CONCOR)</li>
</ul>

cluster: Methods for equivalence clustering

Description

Usage

Arguments

Functions

References