{
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  "Title": "Bayesian Group Sparse Multi-Task Regression",
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  "Description": "Implementation of Bayesian multi-task regression models\nand was developed within the context of imaging genetics. The\npackage can currently fit two models. The Bayesian group sparse\nmulti-task regression model of Greenlaw et al.\n(2017)<doi:10.1093/bioinformatics/btx215> can be fit with\nimplementation using Gibbs sampling. An extension of this model\ndeveloped by Song, Ge et al. to accommodate both spatial\ncorrelation as well as correlation across brain hemispheres can\nalso be fit using either mean-field variational Bayes or Gibbs\nsampling. The model can also be used more generally for\nmultivariate (non-imaging) phenotypes with spatial correlation.",
  "Author": "Yin Song, Shufei Ge, Liangliang Wang, Jiguo Cao, Keelin\nGreenlaw, Mary Lesperance, Farouk S. Nathoo",
  "Maintainer": "Yin Song <yinsong@uvic.ca>",
  "License": "GPL-2",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.0.0",
  "NeedsCompilation": "no",
  "biocViews": "",
  "Packaged": {
    "Date": "2026-05-14 19:37:45 UTC",
    "User": "root"
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  "Repository": "https://cranhaven.r-universe.dev",
  "Date/Publication": "2026-05-14 13:02:00 UTC",
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