xrnet
Hierarchical Regularized Regression
Fits hierarchical regularized regression models to incorporate potentially informative external data, Weaver and Lewinger (2019) <doi:10.21105/joss.01761>. Utilizes coordinate descent to efficiently fit regularized regression models both with and without external information with the most common penalties used in practice (i.e. ridge, lasso, elastic net). Support for standard R matrices, sparse matrices and big.matrix objects.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | xrnet_1.0.1.tar.gz |
518.8 KiB |
1.0.1 |
rolling linux/noble R-4.5 | xrnet_1.0.1.tar.gz |
522.5 KiB |
1.0.1 |
rolling source/ R- | xrnet_1.0.1.tar.gz |
356.2 KiB |
1.0.1 |
latest linux/jammy R-4.5 | xrnet_1.0.1.tar.gz |
518.8 KiB |
1.0.1 |
latest linux/noble R-4.5 | xrnet_1.0.1.tar.gz |
522.5 KiB |
1.0.1 |
latest source/ R- | xrnet_1.0.1.tar.gz |
356.2 KiB |
1.0.1 |
2026-04-26 source/ R- | xrnet_1.0.1.tar.gz |
356.2 KiB |
1.0.1 |
2026-04-23 source/ R- | xrnet_1.0.1.tar.gz |
356.2 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | xrnet_1.0.1.zip |
820.1 KiB |
1.0.0 |
2025-04-20 source/ R- | xrnet_1.0.0.tar.gz |
356.2 KiB |