Package: netrankr
Type: Package
Title: Analyzing Partial Rankings in Networks
Version: 0.2.1
Authors@R: c(
    person("David", "Schoch", email = "david.schoch@manchester.ac.uk", role = c("aut", "cre")),
    person("Julian","Müller", email = "julian.mueller@gess.ethz.ch", role = "ctb"))
Description: 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>.
URL: https://schochastics.github.io/netrankr
BugReports: https://github.com/schochastics/netrankr/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.1)
Imports: igraph (>= 1.0.1), Rcpp (>= 0.12.8)
LinkingTo: Rcpp,RcppArmadillo
SystemRequirements: C++11
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, magrittr, ggplot2, testthat, shiny (>=
        0.13), miniUI (>= 0.1.1), rstudioapi (>= 0.5)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-09-17 18:49:34 UTC; david
Author: David Schoch [aut, cre],
  Julian Müller [ctb]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>
Repository: CRAN
Date/Publication: 2018-09-18 08:20:03 UTC
Built: R 4.0.0; x86_64-w64-mingw32; 2020-04-10 06:34:04 UTC; windows
Archs: i386, x64
