Nonparametric Varying Coefficient Spike-and-Slab Lasso
Overview
Fits Bayesian regularized varying coefficient models with the Nonparametric Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) https://jmlr.org/papers/volume24/20-1437/20-1437.pdf. 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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 4
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 96%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 3.0Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 2.0
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.02020-06-09
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-06-09
- Total releases
- 3 / 6 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.6.0
- Bundled data
- 335 KB / 1 file
- Download size
- 353 KB
Cite
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