SVEMnet
Self-Validated Ensemble Models with Lasso and Relaxed Elastic Net Regression
Tools for fitting self-validated ensemble models (SVEM; Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) in small-sample design-of-experiments and related workflows, using elastic net and relaxed elastic net regression via 'glmnet' (Friedman et al. (2010) <doi:10.18637/jss.v033.i01>). Fractional random-weight bootstraps with anti-correlated validation copies are used to tune penalty paths by validation-weighted AIC/BIC. Supports Gaussian and binomial responses, deterministic expansion helpers for shared factor spaces, prediction with bootstrap uncertainty, and a random-search optimizer that respects mixture constraints and combines multiple responses via desirability functions. Also includes a permutation-based whole-model test for Gaussian SVEM fits (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>). Package code was drafted with assistance from generative AI tools.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
3.2.0 |
rolling linux/jammy R-4.5 | SVEMnet_3.2.0.tar.gz |
460.4 KiB |
3.2.0 |
rolling linux/noble R-4.5 | SVEMnet_3.2.0.tar.gz |
460.4 KiB |
3.2.0 |
rolling source/ R- | SVEMnet_3.2.0.tar.gz |
155.2 KiB |
3.2.0 |
latest linux/jammy R-4.5 | SVEMnet_3.2.0.tar.gz |
460.4 KiB |
3.2.0 |
latest linux/noble R-4.5 | SVEMnet_3.2.0.tar.gz |
460.4 KiB |
3.2.0 |
latest source/ R- | SVEMnet_3.2.0.tar.gz |
155.2 KiB |
3.2.0 |
2026-04-26 source/ R- | SVEMnet_3.2.0.tar.gz |
155.2 KiB |
3.2.0 |
2026-04-23 source/ R- | SVEMnet_3.2.0.tar.gz |
155.2 KiB |
3.2.0 |
2026-04-09 windows/windows R-4.5 | SVEMnet_3.2.0.zip |
463.8 KiB |
1.3.0 |
2025-04-20 source/ R- | SVEMnet_1.3.0.tar.gz |
201.2 KiB |