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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>.

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conda 827.5 kB | win-64/r-netrankr-0.2.1-r36h796a38f_0.tar.bz2  5 years and 3 months ago 0 main
conda 797.4 kB | osx-64/r-netrankr-0.2.1-r36h466af19_0.tar.bz2  5 years and 3 months ago 0 main
conda 822.3 kB | linux-64/r-netrankr-0.2.1-r36h29659fb_0.tar.bz2  5 years and 3 months ago 0 main

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