Package: mBvs 1.92

Kyu Ha Lee

mBvs: Bayesian Variable Selection Methods for Multivariate Data

Bayesian variable selection methods for data with multivariate responses and multiple covariates. The package contains implementations of multivariate Bayesian variable selection methods for continuous data (Lee et al., Biometrics, 2017 <doi:10.1111/biom.12557>) and zero-inflated count data (Lee et al., Biostatistics, 2020 <doi:10.1093/biostatistics/kxy067>).

Authors:Kyu Ha Lee, Mahlet G. Tadesse, Brent A. Coull, Jacqueline R. Starr

mBvs_1.92.tar.gz
mBvs_1.92.zip(r-4.7-x86_64)mBvs_1.92.zip(r-4.7-arm64)mBvs_1.92.zip(r-4.6-x86_64)mBvs_1.92.zip(r-4.6-arm64)
mBvs_1.92.tar.gz(r-4.7-arm64)mBvs_1.92.tar.gz(r-4.7-x86_64)mBvs_1.92.tar.gz(r-4.6-arm64)mBvs_1.92.tar.gz(r-4.6-x86_64)
mBvs_1.92.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mBvs/json (API)

# Install 'mBvs' in R:
install.packages('mBvs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • gsl– GNU Scientific Library (GSL)
Datasets:
  • simData_cont - A simulated data set containing multivariate normal responses and continuous covariates
  • simData_mzip - A simulated data set containing multivariate zero-inflated count responses and a continuous covariate

On CRAN:

Conda:

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

gsl

1.00 score 4 scripts 290 downloads 4 exports 1 dependencies

Last updated from:9589167444. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK81
linux-devel-x86_64OK108
source / vignettesOK151
linux-release-arm64OK111
linux-release-x86_64OK94
windows-devel-arm64OK212
windows-devel-x86_64OK98
windows-release-arm64OK202
windows-release-x86_64OK88
wasm-releaseOK90

Exports:initiate_startValuesmmzipBvsmvnBvsmzipBvs

Dependencies:mvtnorm