{ "_id": "6a1ebc9db25058d4daae1812", "Package": "greed", "Type": "Package", "Title": "Clustering and Model Selection with the Integrated\nClassification Likelihood", "Version": "0.6.2", "Date": "2025-08-28", "Authors@R": "c(person(given = \"Etienne\",\nfamily = \"Côme\",\nrole = c(\"aut\", \"cre\"),\nemail = \"etienne.come@univ-eiffel.fr\"),\nperson(given = \"Nicolas\",\nfamily = \"Jouvin\",\nrole = c(\"aut\")))", "URL": "https://comeetie.github.io/greed/,\nhttps://github.com/comeetie/greed", "BugReports": "https://github.com/comeetie/greed/issues", "Maintainer": "Etienne Côme ", "Description": "An ensemble of algorithms that enable the clustering of\nnetworks and data matrices (such as counts, categorical or\ncontinuous) with different type of generative models. Model\nselection and clustering is performed in combination by\noptimizing the Integrated Classification Likelihood (which is\nequivalent to minimizing the description length). Several\nmodels are available such as: Stochastic Block Model, degree\ncorrected Stochastic Block Model, Mixtures of Multinomial,\nLatent Block Model. 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