Package: baygel 0.3.0

Jarod Smith

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.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://cran.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

1.00 score 2 scripts 194 downloads 7 exports 3 dependencies

Last updated from:50a1991e2d. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK151
linux-devel-x86_64OK143
source / vignettesOK202
linux-release-arm64OK156
linux-release-x86_64OK145
wasm-releaseOK134

Exports:blockBAGENIblockBAGENIIblockBAGLblockBAGRblockBGENblockBGLblockBGR

Dependencies:RcppRcppArmadilloRcppProgress