Package: VBMS 1.0.0

VBMS: Variational Bayesian Algorithm for Multi-Source Heterogeneous Models

A Variational Bayesian algorithm for high-dimensional multi-source heterogeneous linear models. More details have been written up in a paper submitted to the journal Statistics in Medicine, and the details of variational Bayesian methods can be found in Ray and Szabo (2021) <doi:10.1080/01621459.2020.1847121>. It simultaneously performs parameter estimation and variable selection. The algorithm supports two model settings: (1) local models, where variable selection is only applied to homogeneous coefficients, and (2) global models, where variable selection is also performed on heterogeneous coefficients. Two forms of Spike-and-Slab priors are available: the Laplace distribution and the Gaussian distribution as the Slab component.

Authors:Lu Luo [aut, cre], Huiqiong Li [aut]

VBMS_1.0.0.tar.gz
VBMS_1.0.0.zip(r-4.7)VBMS_1.0.0.zip(r-4.6)VBMS_1.0.0.zip(r-4.5)
VBMS_1.0.0.tgz(r-4.6-any)VBMS_1.0.0.tgz(r-4.5-any)
VBMS_1.0.0.tar.gz(r-4.7-any)VBMS_1.0.0.tar.gz(r-4.6-any)
VBMS_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
VBMS/json (API)

# Install 'VBMS' in R:
install.packages('VBMS', repos = c('https://luluo1999.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

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

1.00 score 114 downloads 1 exports 18 dependencies

Last updated from:48cbc7dee9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK105
source / vignettesOK189
linux-release-x86_64OK103
macos-release-arm64OK147
macos-oldrel-arm64OK157
windows-develOK76
windows-releaseOK67
windows-oldrelOK57
wasm-releaseOK94

Exports:vbms

Dependencies:adaptMCMCcodacodetoolsforeachglmnetintervalsiteratorslatticeMASSMatrixpracmaramcmcRcppRcppArmadilloRcppEigenselectiveInferenceshapesurvival