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

bgsmtr_0.7.tar.gz
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bgsmtr_0.7.tgz(r-4.4-any)bgsmtr_0.7.tgz(r-4.3-any)
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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.

1.00 score 6 scripts 270 downloads 3 exports 24 dependencies

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

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winNOTENov 16 2024
R-4.5-linuxNOTENov 16 2024
R-4.4-winNOTENov 16 2024
R-4.4-macNOTENov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:bgsmtrsp_bgsmtrsp_bgsmtr_path

Dependencies:CholWishartcodacodetoolscorpcordigestEDISONforeachglmnetinlineiteratorsLaplacesDemonlatticeMASSMatrixmatrixcalcmiscToolsmnormtmvtnormRcppRcppEigenshapesparseMVNstatmodsurvival