Package: SVEMnet
Type: Package
Title: Self-Validated Ensemble Models with Lasso and Relaxed Elastic
        Net Regression
Version: 2.2.4
Date: 2025-09-25
Authors@R: 
    person(given = "Andrew T.",
           family = "Karl",
           email = "akarl@asu.edu",
           role = c("cre", "aut"),
           comment = c(ORCID = "0000-0002-5933-8706"))
Description: 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>).
Depends: R (>= 3.5.0)
Imports: glmnet (>= 4.1-2), stats, cluster, ggplot2, lhs, foreach,
        doParallel, parallel, gamlss, gamlss.dist
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0), withr, vdiffr
VignetteBuilder: knitr
License: GPL-2 | GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
Config/testthat/edition: 3
LazyData: true
NeedsCompilation: no
Packaged: 2025-09-25 23:10:29 UTC; andre
Author: Andrew T. Karl [cre, aut] (ORCID:
    <https://orcid.org/0000-0002-5933-8706>)
Maintainer: Andrew T. Karl <akarl@asu.edu>
Repository: CRAN
Date/Publication: 2025-09-26 07:20:10 UTC
