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'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

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

openblascpp

1.70 score 120 downloads 5 exports 35 dependencies

Last updated 5 years agofrom:a014847175. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 09 2025
R-4.5-linux-x86_64OKJan 09 2025

Exports:beta_distmmvbvsplot_betaplot_gammaplot_sigma

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshapereshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr