plot.netrankr_mcmc

Plots the result of an object obtained from mcmc_rank_prob

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

plot.netrankr_mcmc function

<dl><dt>x</dt>
<dd>A netrankr_mcmc object</dd>
<dt>icols</dt>
<dd>a list of colors (an internal)</dd>
<dt>bcol</dt>
<dd>color used for the barcharts</dd>
<dt>...</dt>
<dd>additional plot parameters</dd></dl>

Arguments

Author

Plot netrankr_mcmc object — plot.netrankr_mcmc

<dl>

<dt>x</dt>
<dd>A netrankr_mcmc object</dd>


<dt>icols</dt>
<dd>a list of colors (an internal)</dd>


<dt>bcol</dt>
<dd>color used for the barcharts</dd>


<dt>...</dt>
<dd>additional plot parameters</dd>

</dl>

plot.netrankr_mcmc: Plot netrankr_mcmc object

Description

Usage

Arguments

Author