random_sparse_matrix

Build a sparse matrix of size <code>m * n</code> with
non-zero probability <code>p</code>.
Edge weights can be unweighted, constant-weighted or
Poisson-weighted.

Tools for spectral clustering of weighted directed networks using motif
adjacency matrices. Methods perform well on large and sparse networks, and
random sampling methods for generating weighted directed networks are also
provided. Based on methodology detailed in Underwood, Elliott and Cucuringu
(2020) <arXiv:2004.01293>.

William George Underwood

motifcluster

Motif-Based Spectral Clustering of Weighted Directed Networks

random_sparse_matrix function

<dl><dt>m, n</dt>
<dd>Dimension of matrix to build is <code>(m, n)</code>.</dd>
<dt>p</dt>
<dd>Probability that each entry is non-zero (before weighting).</dd>
<dt>sample_weight_type</dt>
<dd>Type of weighting scheme.</dd>
<dt>w</dt>
<dd>Weight parameter.</dd></dl>

Arguments

Build a random sparse matrix — random_sparse_matrix

<dl>

<dt>m, n</dt>
<dd>Dimension of matrix to build is <code>(m, n)</code>.</dd>


<dt>p</dt>
<dd>Probability that each entry is non-zero (before weighting).</dd>


<dt>sample_weight_type</dt>
<dd>Type of weighting scheme.</dd>


<dt>w</dt>
<dd>Weight parameter.</dd>

</dl>

random_sparse_matrix: Build a random sparse matrix

Description

Usage

Value

Arguments