Package: baygel 0.3.0

baygel: Bayesian Shrinkage Estimators for Precision Matrices in Gaussian Graphical Models

This R package offers block Gibbs samplers for the Bayesian (adaptive) graphical lasso, ridge, and naive elastic net priors. These samplers facilitate the simulation of the posterior distribution of precision matrices for Gaussian distributed data and were originally proposed by: Wang (2012) <doi:10.1214/12-BA729>; Smith et al. (2022) <doi:10.48550/arXiv.2210.16290> and Smith et al. (2023) <doi:10.48550/arXiv.2306.14199>, respectively.

Authors:Jarod Smith [aut, cre], Mohammad Arashi [aut], Andriette Bekker [aut]

baygel_0.3.0.tar.gz
baygel_0.3.0.zip(r-4.7)baygel_0.3.0.zip(r-4.6)baygel_0.3.0.zip(r-4.5)
baygel_0.3.0.tgz(r-4.6-x86_64)baygel_0.3.0.tgz(r-4.6-arm64)baygel_0.3.0.tgz(r-4.5-x86_64)baygel_0.3.0.tgz(r-4.5-arm64)
baygel_0.3.0.tar.gz(r-4.7-arm64)baygel_0.3.0.tar.gz(r-4.7-x86_64)baygel_0.3.0.tar.gz(r-4.6-arm64)baygel_0.3.0.tar.gz(r-4.6-x86_64)
baygel_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
baygel/json (API)

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

Bug tracker:https://github.com/jarod-smithy/baygel/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

2.70 score 1 stars 2 scripts 208 downloads 8 exports 5 dependencies

Last updated from:2484b8b487. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK164
linux-devel-x86_64OK144
source / vignettesOK205
linux-release-arm64OK147
linux-release-x86_64OK142
macos-release-arm64OK180
macos-release-x86_64OK343
macos-oldrel-arm64OK223
macos-oldrel-x86_64OK514
windows-develOK159
windows-releaseOK161
windows-oldrelOK160
wasm-releaseOK139

Exports:blockBAEblockBAGENIblockBAGENIIblockBAGLblockBAGRblockBGENblockBGLblockBGR

Dependencies:pracmaRcppRcppArmadilloRcppProgressstatmod