Package: SVEMnet
Type: Package
Title: Self-Validated Ensemble Models with Elastic Net Regression
Version: 1.3.0
Date: 2024-12-21
Authors@R: 
    person(given = "Andrew T.",
           family = "Karl",
           email = "akarl@asu.edu",
           role = c("cre", "aut"),
           comment = c(ORCID = "0000-0002-5933-8706"))
Maintainer: Andrew T. Karl <akarl@asu.edu>
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. <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.
Depends: R (>= 3.5.0)
Imports: glmnet, stats, gamlss, gamlss.dist, ggplot2, lhs, doParallel,
        parallel, foreach
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
License: GPL-2 | GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2024-12-21 18:57:39 UTC; andre
Author: Andrew T. Karl [cre, aut] (<https://orcid.org/0000-0002-5933-8706>)
Repository: CRAN
Date/Publication: 2024-12-21 19:10:02 UTC
