bootstrap_cliques

bootstrap_cliques.tna

Bootstrap Cliques of Transition Networks from Sequence Data

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)

bootstrap_cliques function

<dl><dt>x</dt>
<dd>A <code>tna</code> or a <code>group_tna</code> object.</dd>
<dt>size</dt>
<dd>An <code>integer</code> specifying the size of the cliques to identify.
Defaults to <code>2</code> (dyads).</dd>
<dt>threshold</dt>
<dd>A <code>numeric</code> value that sets the minimum edge weight
for an edge to be considered in the clique. Edges below this value
are ignored. Defaults to <code>0</code>.</dd>
<dt>iter</dt>
<dd>An <code>integer</code> specifying the number of bootstrap samples to
draw. Defaults to <code>1000</code>.</dd>
<dt>level</dt>
<dd>A <code>numeric</code> value representing the significance level for
hypothesis testing and confidence intervals. Defaults to <code>0.05</code>.</dd>
<dt>consistency_range</dt>
<dd>A <code>numeric</code> vector of length 2. Determines how much
the edge weights may deviate (multiplicatively) from their observed values
(below and above) before they are considered insignificant. The default is
<code>c(0.75, 1.25)</code> which corresponds to a symmetric 25% deviation range. Used
only when <code>method = "stability"</code>.</dd></dl>

Arguments

Bootstrap Cliques of Transition Networks from Sequence Data — bootstrap_cliques

<dl>

<dt>x</dt>
<dd>A <code>tna</code> or a <code>group_tna</code> object.</dd>


<dt>size</dt>
<dd>An <code>integer</code> specifying the size of the cliques to identify.
Defaults to <code>2</code> (dyads).</dd>


<dt>threshold</dt>
<dd>A <code>numeric</code> value that sets the minimum edge weight
for an edge to be considered in the clique. Edges below this value
are ignored. Defaults to <code>0</code>.</dd>


<dt>iter</dt>
<dd>An <code>integer</code> specifying the number of bootstrap samples to
draw. Defaults to <code>1000</code>.</dd>


<dt>level</dt>
<dd>A <code>numeric</code> value representing the significance level for
hypothesis testing and confidence intervals. Defaults to <code>0.05</code>.</dd>


<dt>consistency_range</dt>
<dd>A <code>numeric</code> vector of length 2. Determines how much
the edge weights may deviate (multiplicatively) from their observed values
(below and above) before they are considered insignificant. The default is
<code>c(0.75, 1.25)</code> which corresponds to a symmetric 25% deviation range. Used
only when <code>method = "stability"</code>.</dd>

</dl>

bootstrap_cliques: Bootstrap Cliques of Transition Networks from Sequence Data

Description

Usage

Arguments