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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 |
DOI: | 10.32614/CRAN.package.MMVBVS |
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 |
Reference manual: | MMVBVS.pdf |
Package source: | MMVBVS_0.8.0.tar.gz |
Windows binaries: | r-devel: MMVBVS_0.8.0.zip, r-release: MMVBVS_0.8.0.zip, r-oldrel: MMVBVS_0.8.0.zip |
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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.