SVEMnet: Self-Validated Ensemble Models with Lasso and Relaxed Elastic Net Regression

Implements Self-Validated Ensemble Models (SVEM; Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) using elastic net regression via 'glmnet' (Friedman et al. (2010) <doi:10.18637/jss.v033.i01>). SVEM averages predictions from multiple models fitted to fractionally weighted bootstraps of the data, tuned with anti-correlated validation weights. Also implements the randomized permutation whole-model test for SVEM (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>).

Version:	2.3.1
Depends:	R (≥ 3.5.0)
Imports:	glmnet (≥ 4.1-4), stats, cluster, ggplot2, lhs, foreach, doParallel, parallel, gamlss, gamlss.dist
Suggests:	covr, knitr, rmarkdown, testthat (≥ 3.0.0), withr, vdiffr
Published:	2025-10-13
DOI:	10.32614/CRAN.package.SVEMnet
Author:	Andrew T. Karl [cre, aut]
Maintainer:	Andrew T. Karl <akarl at asu.edu>
License:	GPL-2 | GPL-3
NeedsCompilation:	no
Citation:	SVEMnet citation info
Materials:	NEWS
CRAN checks:	SVEMnet results

Documentation:

Reference manual:	SVEMnet.html , SVEMnet.pdf
Vignettes:	SVEMnet Vignette (source, R code)

Downloads:

Package source:	SVEMnet_2.3.1.tar.gz
Windows binaries:	r-devel: SVEMnet_2.3.1.zip, r-release: SVEMnet_2.3.1.zip, r-oldrel: SVEMnet_2.3.1.zip
macOS binaries:	r-release (arm64): SVEMnet_2.3.1.tgz, r-oldrel (arm64): SVEMnet_2.3.1.tgz, r-release (x86_64): SVEMnet_2.3.1.tgz, r-oldrel (x86_64): SVEMnet_2.3.1.tgz
Old sources:	SVEMnet archive

Linking:

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