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. <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>). \\Code for the whole model test was taken from the supplementary material of Karl (2024). Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.
Version: 1.3.0 Depends: R (≥ 3.5.0) Imports: glmnet, stats, gamlss, gamlss.dist, ggplot2, lhs, doParallel, parallel, foreach Suggests: knitr, rmarkdown Published: 2024-12-21 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: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=SVEMnet to link to this page.
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