Package: MMVBVS 0.8.0

Tae Kim

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>.

Authors:Tae Kim

MMVBVS_0.8.0.tar.gz
MMVBVS_0.8.0.tar.gz(r-4.5-noble)MMVBVS_0.8.0.tar.gz(r-4.4-noble)
MMVBVS_0.8.0.tgz(r-4.4-emscripten)MMVBVS_0.8.0.tgz(r-4.3-emscripten)
MMVBVS.pdf |MMVBVS.html✨
MMVBVS/json (API)

# Install 'MMVBVS' in R:
install.packages('MMVBVS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

openblascpp

1.70 score 142 downloads 5 exports 35 dependencies

Last updated 5 years agofrom:a014847175. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 10 2025
R-4.5-linux-x86_64OKMar 10 2025
R-4.4-linux-x86_64OKMar 10 2025

Exports:beta_distmmvbvsplot_betaplot_gammaplot_sigma

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshapereshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr