Package: gigg 0.2.1

Michael Kleinsasser

gigg: Group Inverse-Gamma Gamma Shrinkage for Sparse Regression with Grouping Structure

A Gibbs sampler corresponding to a Group Inverse-Gamma Gamma (GIGG) regression model with adjustment covariates. Hyperparameters in the GIGG prior specification can either be fixed by the user or can be estimated via Marginal Maximum Likelihood Estimation. Jonathan Boss, Jyotishka Datta, Xin Wang, Sung Kyun Park, Jian Kang, Bhramar Mukherjee (2021) <arxiv:2102.10670>.

Authors:Jon Boss [aut], Bhramar Mukherjee [aut], Michael Kleinsasser [cre]

gigg_0.2.1.tar.gz
gigg_0.2.1.tar.gz(r-4.7-arm64)gigg_0.2.1.tar.gz(r-4.7-x86_64)gigg_0.2.1.tar.gz(r-4.6-arm64)gigg_0.2.1.tar.gz(r-4.6-x86_64)
gigg_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
gigg/json (API)

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

Bug tracker:https://github.com/umich-cphds/gigg/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

1.70 score 2 scripts 207 downloads 1 exports 3 dependencies

Last updated from:f84b9a3af3. Checks:4 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE128
linux-devel-x86_64NOTE130
source / vignettesOK168
linux-release-arm64NOTE130
linux-release-x86_64NOTE134
wasm-releaseOK118

Exports:gigg

Dependencies:BHRcppRcppArmadillo