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:
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-4.5-x86_64)MMVBVS_0.8.0.tgz(r-4.5-arm64)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')) |
Bug tracker:https://github.com/tk382/mmvbvs/issues
Last updated 5 years agofrom:ec2c5706c2. Checks:12 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 04 2025 |
R-4.5-win-x86_64 | OK | Mar 04 2025 |
R-4.5-mac-x86_64 | OK | Mar 04 2025 |
R-4.5-mac-aarch64 | OK | Mar 04 2025 |
R-4.5-linux-x86_64 | OK | Mar 04 2025 |
R-4.4-win-x86_64 | OK | Mar 04 2025 |
R-4.4-mac-x86_64 | OK | Mar 04 2025 |
R-4.4-mac-aarch64 | OK | Mar 04 2025 |
R-4.4-linux-x86_64 | OK | Mar 04 2025 |
R-4.3-win-x86_64 | OK | Mar 04 2025 |
R-4.3-mac-x86_64 | OK | Mar 04 2025 |
R-4.3-mac-aarch64 | OK | Mar 04 2025 |
Exports:beta_distmmvbvsplot_betaplot_gammaplot_sigma
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshapereshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr