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Fits group-regularized generalized linear models (GLMs) using the spike-and-slab group lasso (SSGL) prior introduced by 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, Poisson regression, negative binomial regression, and gamma regression. Stand-alone functions for group-regularized negative binomial regression and group-regularized gamma regression are also available, with the option of employing the group lasso penalty of Yuan and Lin (2006) <doi:10.1111/j.1467-9868.2005.00532.x>, the group minimax concave penalty (MCP) of Breheny and Huang <doi:10.1007/s11222-013-9424-2>, or the group smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) <doi:10.1007/s11222-013-9424-2>.
Version: | 1.0 |
Depends: | R (≥ 3.6.0) |
Imports: | stats, MASS, pracma, grpreg |
Published: | 2023-06-27 |
DOI: | 10.32614/CRAN.package.SSGL |
Author: | Ray Bai |
Maintainer: | Ray Bai <raybaistat at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | yes |
CRAN checks: | SSGL results |
Reference manual: | SSGL.pdf |
Package source: | SSGL_1.0.tar.gz |
Windows binaries: | r-devel: SSGL_1.0.zip, r-release: SSGL_1.0.zip, r-oldrel: SSGL_1.0.zip |
macOS binaries: | r-release (arm64): SSGL_1.0.tgz, r-oldrel (arm64): SSGL_1.0.tgz, r-release (x86_64): SSGL_1.0.tgz, r-oldrel (x86_64): SSGL_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.