NVCSSL: Nonparametric Varying Coefficient Spike-and-Slab Lasso

Fits Bayesian regularized varying coefficient models with the Nonparametric Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) <doi:10.48550/arXiv.1907.06477>. Functions to fit frequentist penalized varying coefficients are also provided, 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: 2.0
Depends: R (≥ 3.6.0)
Imports: stats, splines, dae, plyr, Matrix, GIGrvg, MASS, MCMCpack, grpreg, mvtnorm
Published: 2023-09-17
Author: Ray Bai
Maintainer: Ray Bai <raybaistat at gmail.com>
License: GPL-3
NeedsCompilation: yes
CRAN checks: NVCSSL results


Reference manual: NVCSSL.pdf


Package source: NVCSSL_2.0.tar.gz
Windows binaries: r-prerel: NVCSSL_2.0.zip, r-release: NVCSSL_2.0.zip, r-oldrel: NVCSSL_2.0.zip
macOS binaries: r-prerel (arm64): NVCSSL_2.0.tgz, r-release (arm64): NVCSSL_2.0.tgz, r-oldrel (arm64): NVCSSL_2.0.tgz, r-prerel (x86_64): NVCSSL_2.0.tgz, r-release (x86_64): NVCSSL_2.0.tgz
Old sources: NVCSSL archive


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