MMVBVS: Missing Multivariate Bayesian Variable Selection

A variable selection tool for multivariate normal variables with missing-at-random values using Bayesian Hierarchical Model. Visualization functions show the posterior distribution of gamma (inclusion variables) and beta (coefficients). Users can also visualize the heatmap of the posterior mean of covariance matrix. Kim, T. Nicolae, D. (2019) <>. Guan, Y. Stephens, M. (2011) <doi:10.1214/11-AOAS455>.

Version: 0.8.0
Imports: Rcpp, reshape, reshape2, ggplot2, rlang
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, MASS
Published: 2019-12-15
DOI: 10.32614/CRAN.package.MMVBVS
Author: Tae Kim
Maintainer: Tae Kim <tk382 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: MMVBVS results


Reference manual: MMVBVS.pdf


Package source: MMVBVS_0.8.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): MMVBVS_0.8.0.tgz, r-oldrel (arm64): MMVBVS_0.8.0.tgz, r-release (x86_64): MMVBVS_0.8.0.tgz, r-oldrel (x86_64): MMVBVS_0.8.0.tgz


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