Package: bgsmtr 0.7

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.

Authors:Yin Song, Shufei Ge, Liangliang Wang, Jiguo Cao, Keelin Greenlaw, Mary Lesperance, Farouk S. Nathoo

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bgsmtr.pdf |bgsmtr.html
bgsmtr/json (API)

# Install 'bgsmtr' in R:
install.packages('bgsmtr', repos = c('https://v2south.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3 exports 0.09 score 24 dependencies 6 scripts 272 downloads

Last updated 5 years agofrom:5c8e59b600. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 17 2024
R-4.5-winNOTESep 17 2024
R-4.5-linuxNOTESep 17 2024
R-4.4-winNOTESep 17 2024
R-4.4-macNOTESep 17 2024
R-4.3-winOKSep 17 2024
R-4.3-macOKSep 17 2024

Exports:bgsmtrsp_bgsmtrsp_bgsmtr_path

Dependencies:CholWishartcodacodetoolscorpcordigestEDISONforeachglmnetinlineiteratorsLaplacesDemonlatticeMASSMatrixmatrixcalcmiscToolsmnormtmvtnormRcppRcppEigenshapesparseMVNstatmodsurvival