netrankr: Analyzing Partial Rankings in Networks
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>.
| Version: |
1.1.1 |
| Depends: |
R (≥ 3.0.1) |
| Imports: |
igraph (≥ 1.0.1), Rcpp (≥ 0.12.8), Matrix |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown, magrittr, testthat, shiny (≥ 0.13), miniUI (≥ 0.1.1), rstudioapi (≥ 0.5) |
| Published: |
2021-12-21 |
| Author: |
David Schoch 
[aut, cre],
Julian Müller [ctb] |
| Maintainer: |
David Schoch <david at schochastics.net> |
| BugReports: |
https://github.com/schochastics/netrankr/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/schochastics/netrankr/ |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++11 |
| Citation: |
netrankr citation info |
| Materials: |
README NEWS |
| CRAN checks: |
netrankr results |
Documentation:
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Reverse dependencies:
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