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  "Title": "Robust Model-Based Clustering",
  "Description": "Performs robust cluster analysis allowing for outliers and\nnoise that cannot be fitted by any cluster. The data are\nmodelled by a mixture of Gaussian distributions and a noise\ncomponent, which is an improper uniform distribution covering\nthe whole Euclidean space. Parameters are estimated by (pseudo)\nmaximum likelihood. This is fitted by a EM-type algorithm. See\nCoretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>,\nand Coretto and Hennig (2017)\n<https://jmlr.org/papers/v18/16-382.html>.",
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  "Date": "2021-05-28",
  "Authors@R": "c(person(\"Pietro\", \"Coretto\",\nrole = c(\"aut\", \"cre\"),\nemail = \"pcoretto@unisa.it\",\ncomment = \"Homepage: <https://pietro-coretto.github.io>\"),\nperson(\"Christian\", \"Hennig\",\nrole = c(\"aut\"),\nemail = \"christian.hennig@unibo.it\",\ncomment = \"Homepage:  <https://www.unibo.it/sitoweb/christian.hennig/en>\")\n)",
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  "Author": "Pietro Coretto [aut, cre] (Homepage:\n<https://pietro-coretto.github.io>), Christian Hennig [aut]\n(Homepage: <https://www.unibo.it/sitoweb/christian.hennig/en>)",
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