stepSplitReg
Stepwise Split Regularized Regression
Functions to perform stepwise split regularized regression. The approach first uses a stepwise algorithm to split the variables into the models with a goodness of fit criterion, and then regularization is applied to each model. The weights of the models in the ensemble are determined based on a criterion selected by the user.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.5 |
rolling linux/jammy R-4.5 | stepSplitReg_1.0.5.tar.gz |
184.2 KiB |
1.0.5 |
rolling linux/noble R-4.5 | stepSplitReg_1.0.5.tar.gz |
189.1 KiB |
1.0.5 |
rolling source/ R- | stepSplitReg_1.0.5.tar.gz |
60.5 KiB |
1.0.5 |
latest linux/jammy R-4.5 | stepSplitReg_1.0.5.tar.gz |
184.2 KiB |
1.0.5 |
latest linux/noble R-4.5 | stepSplitReg_1.0.5.tar.gz |
189.1 KiB |
1.0.5 |
latest source/ R- | stepSplitReg_1.0.5.tar.gz |
60.5 KiB |
1.0.5 |
2026-04-26 source/ R- | stepSplitReg_1.0.5.tar.gz |
60.5 KiB |
1.0.5 |
2026-04-23 source/ R- | stepSplitReg_1.0.5.tar.gz |
60.5 KiB |
1.0.5 |
2026-04-09 windows/windows R-4.5 | stepSplitReg_1.0.5.zip |
501.9 KiB |
1.0.5 |
2025-04-20 source/ R- | stepSplitReg_1.0.5.tar.gz |
60.5 KiB |