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netrankr: Analyzing Partial Rankings in Networks (original) (raw)

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: 1.2.4
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), covr
Published: 2025-02-05
DOI: 10.32614/CRAN.package.netrankr
Author: David Schoch ORCID iD [aut, cre], Julian Müller [ctb]
Maintainer: David Schoch
BugReports: https://github.com/schochastics/netrankr/issues
License: MIT + file
URL: https://github.com/schochastics/netrankr/,https://schochastics.github.io/netrankr/
NeedsCompilation: yes
Citation: netrankr citation info
Materials: README, NEWS
In views: NetworkAnalysis
CRAN checks: netrankr results

Documentation:

Reference manual: netrankr.html , <netrankr.pdf>
Vignettes: 09 benchmarks (source, R code) 05 centrality indices (source, R code) 04 indirect relations in networks (source, R code) 01 neighborhood-inclusion and centrality (source, R code) 06 partial centrality (source, R code) 03 positional dominance in networks (source, R code) 07 probabilistic centrality (source, R code) 02 uniquely ranked graphs (source, R code) 08 use case (source, R code)

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