{ "_id": "6a1f3949b401979e73428eaf", "Package": "MixSim", "Version": "1.1-8", "Date": "2024-07-16", "Title": "Simulating Data to Study Performance of Clustering Algorithms", "Authors@R": "c(person(\"Volodymyr\", \"Melnykov\", role = \"aut\",\nemail = \"vmelnykov@cba.ua.edu\"),\nperson(\"Wei-Chen\", \"Chen\", role = c(\"aut\", \"cre\"),\nemail = \"wccsnow@gmail.com\"),\nperson(\"Ranjan\", \"Maitra\", role = \"aut\",\nemail = \"maitra@iastate.edu\"),\nperson(\"Robert\", \"Davies\", role = \"ctb\",\ncomment = \"quadratic form probabilities\"),\nperson(\"Stephen\", \"Moshier\", role = \"ctb\",\ncomment = \"eigenvalue calculations\"),\nperson(\"Rouben\", \"Rostamian\", role = \"ctb\",\ncomment = \"memory allocation\"))", "LazyLoad": "yes", "Description": "The utility of this package is in simulating mixtures of\nGaussian distributions with different levels of overlap between\nmixture components. Pairwise overlap, defined as a sum of two\nmisclassification probabilities, measures the degree of\ninteraction between components and can be readily employed to\ncontrol the clustering complexity of datasets simulated from\nmixtures. These datasets can then be used for systematic\nperformance investigation of clustering and finite mixture\nmodeling algorithms. Among other capabilities of 'MixSim',\nthere are computing the exact overlap for Gaussian mixtures,\nsimulating Gaussian and non-Gaussian data, simulating outliers\nand noise variables, calculating various measures of agreement\nbetween two partitionings, and constructing parallel\ndistribution plots for the graphical display of finite mixture\nmodels.", "License": "GPL (>= 2)", "NeedsCompilation": "yes", "Maintainer": "Wei-Chen Chen ", "Repository": "https://snoweye.r-universe.dev", "Date/Publication": "2024-07-17 02:54:53 UTC", "RemoteUrl": "https://github.com/snoweye/mixsim", "RemoteRef": "HEAD", "RemoteSha": "f4bb9f34d868f821ceea8bd7f9f29ef4ed0de66e", "Packaged": { "Date": "2026-05-09 07:40:30 UTC", "User": "root" }, "Author": "Volodymyr Melnykov [aut],\nWei-Chen Chen [aut, cre],\nRanjan Maitra [aut],\nRobert Davies [ctb] (quadratic form probabilities),\nStephen Moshier [ctb] (eigenvalue calculations),\nRouben Rostamian [ctb] (memory allocation)", "MD5sum": 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