{ "_id": "6a10355aacfb0bcc41c99a50", "Package": "BCFM", "Type": "Package", "Title": "Bayesian Clustering Factor Models", "Version": "1.0.0", "Authors@R": "c(\nperson(\"Allison\", \"Tegge\", email = \"ategge@vt.edu\", role = \"aut\"),\nperson(\"Marco\", \"Ferreira\", email = \"marf@vt.edu\", role = \"aut\"),\nperson(\"Hwasoo\", \"Shin\", email = \"hshin2@hfhs.org\", role = \"aut\"),\nperson(\"Meriem\", \"Touami\", email = \"meriemt@vt.edu\", role = c(\"aut\", \"cre\")))", "Description": "Implements the Bayesian Clustering Factor Models (BCFM)\nfor simultaneous clustering and latent factor analysis of\nmultivariate longitudinal data. The model accounts for\nwithin-cluster dependence through shared latent factors while\nallowing heterogeneity across clusters, enabling flexible\ncovariance modeling in high-dimensional settings. Inference is\nperformed using Markov chain Monte Carlo (MCMC) methods with\ncomputationally intensive steps implemented via 'Rcpp'. Model\nselection and visualization tools are provided. 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