as.matrix.netrankr_full

extract probabilities as matrices from the result of an object obtained from exact_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

as.matrix.netrankr_full function

<dl><dt>x</dt>
<dd>A netrankr_full object</dd>
<dt>type</dt>
<dd>which probabilities to return. "rank" for rank probabilities, "relative" for relative rank probabilities and "expected" for expected rank probabilities and their variants</dd>
<dt>...</dt>
<dd>additional parameters for as.matrix</dd></dl>

Arguments

Author

Extract probabilities from netrankr_full object — as.matrix.netrankr_full

<dl>

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


<dt>type</dt>
<dd>which probabilities to return. "rank" for rank probabilities, "relative" for relative rank probabilities and "expected" for expected rank probabilities and their variants</dd>


<dt>...</dt>
<dd>additional parameters for as.matrix</dd>

</dl>

as.matrix.netrankr_full: Extract probabilities from netrankr_full object

Description

Usage

Arguments

Author