Package: MMVBVS 0.8.0

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.zip(r-4.5)MMVBVS_0.8.0.zip(r-4.4)MMVBVS_0.8.0.zip(r-4.3)
MMVBVS_0.8.0.tgz(r-4.4-x86_64)MMVBVS_0.8.0.tgz(r-4.4-arm64)MMVBVS_0.8.0.tgz(r-4.3-x86_64)MMVBVS_0.8.0.tgz(r-4.3-arm64)
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://tk382.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tk382/mmvbvs/issues

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

On CRAN:

openblascpp

2.70 score 99 downloads 5 exports 35 dependencies

Last updated 5 years agofrom:ec2c5706c2. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 03 2025
R-4.5-win-x86_64OKJan 03 2025
R-4.5-linux-x86_64OKJan 03 2025
R-4.4-win-x86_64OKJan 03 2025
R-4.4-mac-x86_64OKJan 03 2025
R-4.4-mac-aarch64OKJan 03 2025
R-4.3-win-x86_64OKJan 03 2025
R-4.3-mac-x86_64OKJan 03 2025
R-4.3-mac-aarch64OKJan 03 2025

Exports:beta_distmmvbvsplot_betaplot_gammaplot_sigma

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshapereshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr