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.
- Version2.0
- R version≥ 3.6.0
- LicenseGPL-3
- Needs compilation?Yes
- Last release09/17/2023
Team
Ray Bai
Insights
Last 30 days
This package has been downloaded 121 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,966 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 31 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
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Dependencies
- Imports8 packages