Package: bravo 4.1.0

Dongjin Li

bravo: Bayesian Screening and Variable Selection

Performs Bayesian variable screening and selection for ultra-high dimensional linear regression models.Also contains an user friendly web application to perform multi trait GWAS.

Authors:Dongjin Li [aut, cre], Debarshi Chakraborty [aut], Somak Dutta [aut], Vivekananda Roy [ctb]

bravo_4.1.0.tar.gz
bravo_4.1.0.tar.gz(r-4.7-arm64)bravo_4.1.0.tar.gz(r-4.7-x86_64)bravo_4.1.0.tar.gz(r-4.6-arm64)bravo_4.1.0.tar.gz(r-4.6-x86_64)
bravo_4.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
bravo/json (API)

# Install 'bravo' in R:
install.packages('bravo', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • 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.

cpp

2.00 score 4 scripts 793 downloads 10 exports 46 dependencies

Last updated from:343f2f3d77. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK144
source / vignettesOK188
linux-release-arm64OK154
linux-release-x86_64OK148
wasm-releaseOK111

Exports:bitscalc.runtimedense_to_sparse_converterdense2sparsemip.svenparameter_selectionpredict.svensvensveneticssvenetics_pipeline

Dependencies:base64encbslibcachemclicodetoolscommonmarkdigestdoParalleldplyrfastmapfontawesomeforeachfsgenericsgluehtmltoolshttpuviteratorsjquerylibjsonlitelaterlatticelifecyclemagrittrMatrixmemoisememusemimeotelpillarpkgconfigpromisesR6rappdirsRcpprlangsassshinyshinyjssourcetoolstibbletidyselectutf8vctrswithrxtable