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  "Date": "2025-1-6",
  "Title": "Clustering with Matrix Gaussian and Matrix Transformation\nMixture Models",
  "Authors@R": "c(person(\"Xuwen\", \"Zhu\", role = c(\"aut\", \"cre\"),\nemail = \"xzhu20@ua.edu\"),\nperson(\"Volodymyr\", \"Melnykov\", role = \"aut\"),\nperson(\"Shuchismita\", \"Sarkar\", role = \"ctb\"),\nperson(\"Michael\", \"Hutt\", role = c(\"ctb\", \"cph\")),\nperson(\"Stephen\", \"Moshier\", role = c(\"ctb\", \"cph\")),\nperson(\"Rouben\", \"Rostamian\", role = c(\"ctb\", \"cph\")),\nperson(\"Carl Edward\", \"Rasmussen\", role = c(\"ctb\", \"cph\")),\nperson(\"Dianne\", \"Cook\", role = c(\"ctb\", \"cph\")))",
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  "Description": "Provides matrix Gaussian mixture models, matrix\ntransformation mixture models and their model-based clustering\nresults. The parsimonious models of the mean matrices and\nvariance covariance matrices are implemented with a total of\n196 variations. For more information, please check: Xuwen Zhu,\nShuchismita Sarkar, and Volodymyr Melnykov (2021),\n\"MatTransMix: an R package for matrix model-based clustering\nand parsimonious mixture modeling\",\n<doi:10.1007/s00357-021-09401-9>.",
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