sim.fluency

Simulates verbal fluency data based on the number of
nodes in the desired network. The summed total of
each response is simulated from a poisson distribution 
(see <code><a href="/link/rpois?package=SemNeT&version=1.4.4" data-mini-rdoc="SemNeT::rpois">rpois</a></code>), using frequencies from the
<code>animals.freq</code> data. Using these
sums, participants responses are simulated with a probability of giving
a response as the total of the summed response over the number of participants.

Implements several functions for the analysis of semantic networks including different network estimation algorithms, partial node bootstrapping (Kenett, Anaki, & Faust, 2014 <doi:10.3389/fnhum.2014.00407>), random walk simulation (Kenett & Austerweil, 2016 <http://alab.psych.wisc.edu/papers/files/Kenett16CreativityRW.pdf>), and a function to compute global network measures. Significance tests and plotting features are also implemented.

Alexander Christensen

SemNeT

Methods and Measures for Semantic Network Analysis

Alexander P. Christensen

Yoed N. Kenett

sim.fluency function

<dl><dt>nodes</dt>
<dd>Numeric.
Number of nodes to simulate in data.
Defaults to <code>100</code></dd>
<dt>cases</dt>
<dd>Numeric.
Number of participants to simulate in data.
Defaults to <code>500</code></dd>
<dt>random</dt>
<dd>Boolean.
Should the frequencies be randomly sampled from?
Defaults to <code>FALSE</code>.</dd></dl>

Arguments

Alexander Christensen &lt;alexpaulchristensen@gmail.com&gt;

Author

Simulates verbal fluency data based on the number of
nodes in the desired network. The summed total of
each response is simulated from a poisson distribution 
(see <code><a href='https://rdrr.io/r/stats/Poisson.html'>rpois</a></code>), using frequencies from the
<code>animals.freq</code> data. Using these
sums, participants responses are simulated with a probability of giving
a response as the total of the summed response over the number of participants.

Simulates a verbal fluency binary response matrix — sim.fluency

<dl>

<dt>nodes</dt>
<dd>Numeric.
Number of nodes to simulate in data.
Defaults to <code>100</code></dd>


<dt>cases</dt>
<dd>Numeric.
Number of participants to simulate in data.
Defaults to <code>500</code></dd>


<dt>random</dt>
<dd>Boolean.
Should the frequencies be randomly sampled from?
Defaults to <code>FALSE</code>.</dd>

</dl>

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sim.fluency: Simulates a verbal fluency binary response matrix

Description

Usage

Value

Arguments

Author

Examples

Join us for RADAR: AI Edition

Description

Usage

Value

Arguments

Author

Examples

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