count_contingency_tables_log

Given a contingency table, returns the natural logarithm of the number of
contingency tables that share the same column and row sums. This implementation
combines a Markov Chain Monte Carlo approximation with an analytical formula.
The input can be either M a contingency table, or two vectors of labels c1 and c2 
(in this case, we are counting contingency tables with the same column an row sums as
the one produced by c1 and c2)

Evaluates the stability and significance of clusters on 'igraph' graphs.
Supports weighted and unweighted graphs. Implements the cluster evaluation methods
defined by Arratia A, Renedo M (2021) <doi:10.7717/peerj-cs.600>. Also includes an
implementation of the Reduced Mutual Information introduced by Newman et al. (2020)
<doi:10.1103/PhysRevE.101.042304>.

Martc3<ad> Mirambell

clustAnalytics

Cluster Evaluation on Graphs

count_contingency_tables_log function

<dl><dt>c1, c2</dt>
<dd>membership vectors</dd>
<dt>M</dt>
<dd>contingency table</dd>
<dt>monte_carlo_only</dt>
<dd>Uses only the Monte Carlo approximation</dd></dl>

Arguments

Natural logarithm of the number of contingency tables — count_contingency_tables_log

<dl>

<dt>c1, c2</dt>
<dd>membership vectors</dd>


<dt>M</dt>
<dd>contingency table</dd>


<dt>monte_carlo_only</dt>
<dd>Uses only the Monte Carlo approximation</dd>

</dl>

count_contingency_tables_log: Natural logarithm of the number of contingency tables

Description

Usage

Arguments