spectral_gap

The spectral (or eigen) gap of a graph is the absolute
difference between the biggest and second biggest eigenvalue
of the adjacency matrix. To compare spectral gaps across networks, the fraction can be used.

Implements methods for centrality related analyses of networks.
While the package includes the possibility to build more than 20 indices,
its main focus lies on index-free assessment of centrality via partial
rankings obtained by neighborhood-inclusion or positional dominance. These
partial rankings can be analyzed with different methods, including
probabilistic methods like computing expected node ranks and relative
rank probabilities (how likely is it that a node is more central than another?).
The methodology is described in depth in the vignettes and in
Schoch (2018) <doi:10.1016/j.socnet.2017.12.003>.

David Schoch

netrankr

Analyzing Partial Rankings in Networks

Julian Müller

spectral_gap function

<dl><dt>g</dt>
<dd>igraph object</dd>
<dt>method</dt>
<dd>A string, either "frac" or "abs"</dd></dl>

Arguments

Author

Spectral gap of a graph — spectral_gap

<dl>

<dt>g</dt>
<dd>igraph object</dd>


<dt>method</dt>
<dd>A string, either "frac" or "abs"</dd>

</dl>

spectral_gap: Spectral gap of a graph

Description

Usage

Value

Arguments

Author

Details

Examples