findActiveParam

Finds the active model's parameters

Stochastic blockmodeling of one-mode and linked networks as presented in Škulj and Žiberna (2022) <doi:10.1016/j.socnet.2022.02.001>. The optimization is done via CEM (Classification Expectation Maximization) algorithm that can be initialized by random partitions or the results of k-means algorithm. The development of this package is financially supported by the Slovenian Research Agency (<https://www.arrs.si/>) within the research programs P5-0168 and the research projects J7-8279 (Blockmodeling multilevel and temporal networks) and J5-2557 (Comparison and evaluation of different approaches to blockmodeling dynamic networks by simulations with application to Slovenian co-authorship networks).

Ale<c5><a1> <c5><bd>iberna

StochBlock

Stochastic Blockmodeling of One-Mode and Linked Networks

Aleš Žiberna

Fabio Ashtar Telarico

findActiveParam function

<dl><dt>M</dt>
<dd>matrix</dd>
<dt>n</dt>
<dd>number of units (equal to number of <code>M</code>'s rows)</dd>
<dt>k</dt>
<dd>parameters to retrieve</dd>
<dt>na.rm</dt>
<dd>logical, whether to ignore <code>NA</code> data</dd></dl>

Arguments

Finds the active model's parameters — findActiveParam

<dl>

<dt>M</dt>
<dd>matrix</dd>


<dt>n</dt>
<dd>number of units (equal to number of <code>M</code>'s rows)</dd>


<dt>k</dt>
<dd>parameters to retrieve</dd>


<dt>na.rm</dt>
<dd>logical, whether to ignore <code>NA</code> data</dd>

</dl>

findActiveParam: Finds the active model's parameters

Description

Usage

Value

Arguments