LassoHiDFastGibbs
Fast High-Dimensional Gibbs Samplers for Bayesian Lasso Regression
Provides fast and scalable Gibbs sampling algorithms for Bayesian Lasso regression model in high-dimensional settings. The package implements efficient partially collapsed and nested Gibbs samplers for Bayesian Lasso, with a focus on computational efficiency when the number of predictors is large relative to the sample size. Methods are described at Davoudabadi and Ormerod (2026) <https://github.com/MJDavoudabadi/LassoHiDFastGibbs>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.5 |
rolling linux/jammy R-4.5 | LassoHiDFastGibbs_0.1.5.tar.gz |
663.7 KiB |
0.1.5 |
rolling linux/noble R-4.5 | LassoHiDFastGibbs_0.1.5.tar.gz |
676.7 KiB |
0.1.5 |
rolling source/ R- | LassoHiDFastGibbs_0.1.5.tar.gz |
336.3 KiB |
0.1.5 |
latest linux/jammy R-4.5 | LassoHiDFastGibbs_0.1.5.tar.gz |
663.7 KiB |
0.1.5 |
latest linux/noble R-4.5 | LassoHiDFastGibbs_0.1.5.tar.gz |
676.7 KiB |
0.1.5 |
latest source/ R- | LassoHiDFastGibbs_0.1.5.tar.gz |
336.3 KiB |
0.1.5 |
2026-04-26 source/ R- | LassoHiDFastGibbs_0.1.5.tar.gz |
336.3 KiB |
0.1.5 |
2026-04-23 source/ R- | LassoHiDFastGibbs_0.1.5.tar.gz |
336.3 KiB |
0.1.5 |
2026-04-09 windows/windows R-4.5 | LassoHiDFastGibbs_0.1.5.zip |
1.0 MiB |