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) <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

Documentation:

Reference manual:

NVCSSL.pdf

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=NVCSSL to link to this page.