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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>.

copied from cf-post-staging / r-netrankr
Type Size Name Uploaded Downloads Labels
conda 1.2 MB | win-64/r-netrankr-1.2.1-r41ha856d6a_0.conda  2 years and 2 months ago 562 main
conda 1.2 MB | osx-64/r-netrankr-1.2.1-r43hac7d2d5_0.conda  2 years and 2 months ago 394 main
conda 1.2 MB | osx-64/r-netrankr-1.2.1-r42hac7d2d5_0.conda  2 years and 2 months ago 406 main
conda 1.2 MB | linux-64/r-netrankr-1.2.1-r43ha503ecb_0.conda  2 years and 2 months ago 1968 main
conda 1.2 MB | linux-64/r-netrankr-1.2.1-r42ha503ecb_0.conda  2 years and 2 months ago 1923 main

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