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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