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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-1.2.2-r41ha856d6a_0.conda  1 year and 10 months ago 521 main
conda 1.2 MB | osx-64/r-netrankr-1.2.2-r43h29979af_0.conda  1 year and 10 months ago 453 main
conda 1.2 MB | osx-64/r-netrankr-1.2.2-r42h29979af_0.conda  1 year and 10 months ago 414 main
conda 1.2 MB | linux-64/r-netrankr-1.2.2-r42ha503ecb_0.conda  1 year and 10 months ago 1905 main
conda 1.2 MB | linux-64/r-netrankr-1.2.2-r43ha503ecb_0.conda  1 year and 10 months ago 1831 main

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