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) <https://github.com/tk382/MMVBVS/blob/master/workingpaper.pdf>. 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
Author: Tae Kim
Maintainer: Tae Kim <tk382 at uchicago.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: MMVBVS results

Downloads:

Reference manual: MMVBVS.pdf
Package source: MMVBVS_0.8.0.tar.gz
Windows binaries: r-devel: MMVBVS_0.8.0.zip, r-devel-gcc8: MMVBVS_0.8.0.zip, r-release: MMVBVS_0.8.0.zip, r-oldrel: not available
OS X binaries: r-release: MMVBVS_0.8.0.tgz, r-oldrel: MMVBVS_0.8.0.tgz

Linking:

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