plot_model

Plot a Transition Network Model from a Matrix of Edge Weights

internal

Provides tools for performing Transition Network Analysis (TNA) to
study relational dynamics, including functions for building and plotting TNA
models, calculating centrality measures, and identifying dominant events and
patterns. TNA statistical techniques (e.g., bootstrapping and permutation
tests) ensure the reliability of observed insights and confirm that
identified dynamics are meaningful. See (Saqr et al., 2025)
<doi:10.1145/3706468.3706513> for more details on TNA.

Sonsoles López-Pernas

Transition Network Analysis (TNA)

plot_model function

<dl><dt>x</dt>
<dd>A square <code>matrix</code> of edge weights.</dd>
<dt>labels</dt>
<dd>Optional <code>character</code> vector of node labels.</dd>
<dt>colors</dt>
<dd>An optional <code>character</code> vector of node colors to use.</dd>
<dt>...</dt>
<dd>Additional arguments passed to <code>cograph::splot()</code> or
<code>cograph::plot_htna()</code>.</dd></dl>

Arguments

Plot a Transition Network Model from a Matrix of Edge Weights — plot_model

<dl>

<dt>x</dt>
<dd>A square <code>matrix</code> of edge weights.</dd>


<dt>labels</dt>
<dd>Optional <code>character</code> vector of node labels.</dd>


<dt>colors</dt>
<dd>An optional <code>character</code> vector of node colors to use.</dd>


<dt>...</dt>
<dd>Additional arguments passed to <code>cograph::splot()</code> or
<code>cograph::plot_htna()</code>.</dd>

</dl>

plot_model: Plot a Transition Network Model from a Matrix of Edge Weights

Description

Usage

Value

Arguments

Examples