Package: SSGL 2.0

Ray Bai

SSGL: Spike-and-Slab Group Lasso for Group-Regularized Generalized Linear Models

Fits group-regularized generalized linear models (GLMs) using the spike-and-slab group lasso (SSGL) prior of Bai et al. (2022) <doi:10.1080/01621459.2020.1765784> and extended to GLMs by Bai (2023) <doi:10.48550/arXiv.2007.07021>. This package supports fitting the SSGL model for the following GLMs with group sparsity: Gaussian linear regression, binary logistic regression, and Poisson regression.

Authors:Ray Bai [aut, cre]

SSGL_2.0.tar.gz
SSGL_2.0.tar.gz(r-4.7-any)SSGL_2.0.tar.gz(r-4.6-any)
SSGL_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SSGL/json (API)

# Install 'SSGL' in R:
install.packages('SSGL', repos = c('https://cran.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 1 scripts 193 downloads 3 exports 79 dependencies

Last updated from:2bdabe0fa4. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK168
source / vignettesOK193
linux-release-x86_64OK162
wasm-releaseOK130

Exports:SSGLSSGL_cvSSGL_gibbs

Dependencies:BayesLogitcaretclasscliclockcodetoolscpp11data.tablediagramdigestdoParalleldoRNGdplyre1071farverforeachfuturefuture.applygenericsggplot2GIGrvgglobalsgluegowergrpreggtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrngtoolsrpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr