adj_to_wdnet

Creates a <code>wdnet</code> object using an adjacency matrix

Assortativity coefficients, centrality measures,
and clustering coefficients for weighted and directed networks.
Rewiring unweighted networks with given assortativity coefficients.
Generating general preferential attachment networks.

Yelie Yuan

wdnet

Weighted and Directed Networks

Tiandong Wang

Jun Yan

Panpan Zhang

adj_to_wdnet function

<dl><dt>adj</dt>
<dd>An adjacency matrix used to extract <code>edgelist</code> and
<code>edgeweight</code> using <code>igraph</code>.</dd>
<dt>directed</dt>
<dd>Logical, whether the network is directed (TRUE) or undirected
(FALSE). If <code>adj</code> is asymmetric, the network is directed.</dd>
<dt>weighted</dt>
<dd>Logical, whether the network is weighted (TRUE) or unweighted
(FALSE).</dd>
<dt>nodegroup</dt>
<dd>A numeric vector of node groups.</dd>
<dt>...</dt>
<dd>Additional components to be added to the <code>wdnet</code> object.</dd></dl>

Arguments

Creates a wdnet object using an adjacency matrix — adj_to_wdnet

<dl>

<dt>adj</dt>
<dd>An adjacency matrix used to extract <code>edgelist</code> and
<code>edgeweight</code> using <code>igraph</code>.</dd>


<dt>directed</dt>
<dd>Logical, whether the network is directed (TRUE) or undirected
(FALSE). If <code>adj</code> is asymmetric, the network is directed.</dd>


<dt>weighted</dt>
<dd>Logical, whether the network is weighted (TRUE) or unweighted
(FALSE).</dd>


<dt>nodegroup</dt>
<dd>A numeric vector of node groups.</dd>


<dt>...</dt>
<dd>Additional components to be added to the <code>wdnet</code> object.</dd>

</dl>

adj_to_wdnet: Creates a `wdnet` object using an adjacency matrix

Description

Usage

Value

Arguments

Examples