The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

bgsmtr: Bayesian Group Sparse Multi-Task Regression

Implementation of Bayesian multi-task regression models and was developed within the context of imaging genetics. The package can currently fit two models. The Bayesian group sparse multi-task regression model of Greenlaw et al. (2017)<doi:10.1093/bioinformatics/btx215> can be fit with implementation using Gibbs sampling. An extension of this model developed by Song, Ge et al. to accommodate both spatial correlation as well as correlation across brain hemispheres can also be fit using either mean-field variational Bayes or Gibbs sampling. The model can also be used more generally for multivariate (non-imaging) phenotypes with spatial correlation.

Version: 0.7
Depends: R (≥ 3.5.0), Matrix (≥ 1.2.6), mvtnorm (≥ 1.0.5), matrixcalc (≥ 1.0.3), miscTools (≥ 0.6.22)
Imports: coda (≥ 0.18.1), EDISON (≥ 1.1.1), statmod (≥ 1.4.26), methods (≥ 3.3.3), sparseMVN (> 0.2.0), inline (≥ 0.3.15), LaplacesDemon (≥ 16.1.0), glmnet (≥ 2.0.13), CholWishart (≥ 0.9.3), mnormt (≥ 1.5.4), Rcpp (≥ 0.12.14)
Published: 2019-12-13
DOI: 10.32614/CRAN.package.bgsmtr
Author: Yin Song, Shufei Ge, Liangliang Wang, Jiguo Cao, Keelin Greenlaw, Mary Lesperance, Farouk S. Nathoo
Maintainer: Yin Song <yinsong at uvic.ca>
License: GPL-2
NeedsCompilation: no
CRAN checks: bgsmtr results

Documentation:

Reference manual: bgsmtr.pdf

Downloads:

Package source: bgsmtr_0.7.tar.gz
Windows binaries: r-devel: bgsmtr_0.7.zip, r-release: bgsmtr_0.7.zip, r-oldrel: bgsmtr_0.7.zip
macOS binaries: r-release (arm64): bgsmtr_0.7.tgz, r-oldrel (arm64): bgsmtr_0.7.tgz, r-release (x86_64): bgsmtr_0.7.tgz, r-oldrel (x86_64): bgsmtr_0.7.tgz
Old sources: bgsmtr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bgsmtr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.