{ "_id": "6a103feaacfb0bcc41c9cf83", "Package": "netrankr", "Type": "Package", "Title": "Analyzing Partial Rankings in Networks", "Version": "1.2.4", "Authors@R": "c(\nperson(\"David\", \"Schoch\", email = \"david@schochastics.net\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2952-4812\")),\nperson(\"Julian\",\"Müller\", email = \"julian.mueller@gess.ethz.ch\", role = \"ctb\"))", "Description": "Implements methods for centrality related analyses of\nnetworks. While the package includes the possibility to build\nmore than 20 indices, its main focus lies on index-free\nassessment of centrality via partial rankings obtained by\nneighborhood-inclusion or positional dominance. These partial\nrankings can be analyzed with different methods, including\nprobabilistic methods like computing expected node ranks and\nrelative rank probabilities (how likely is it that a node is\nmore central than another?). 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