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-4.5-noble)SSGL_2.0.tar.gz(r-4.4-noble)
SSGL_2.0.tgz(r-4.4-emscripten)SSGL_2.0.tgz(r-4.3-emscripten)
SSGL.pdf |SSGL.html✨
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 142 downloads 3 exports 82 dependencies

Last updated 12 hours agofrom:2bdabe0fa4. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 24 2025
R-4.5-linuxOKMar 24 2025
R-4.4-linuxOKMar 24 2025

Exports:SSGLSSGL_cvSSGL_gibbs

Dependencies:BayesLogitcaretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdoParalleldoRNGdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2GIGrvgglobalsgluegowergrpreggtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrngtoolsrpartscalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr