Package: nestedcv
Title: Nested Cross-Validation with 'glmnet' and 'caret'
Version: 0.8.4
Authors@R: 
    c(person(given = "Myles",family = "Lewis",
    role = c("aut", "cre"),
    email = "myles.lewis@qmul.ac.uk",
    comment = c(ORCID = "0000-0001-9365-5345")),
    person(given = "Athina",family = "Spiliopoulou",
    role = c("aut"),
    comment = c(ORCID = "0000-0002-5929-6585")),
    person(given = "Cankut",family = "Cubuk",
    role = c("ctb"),
    email = "c.cubuk@qmul.ac.uk",
    comment = c(ORCID = "0000-0003-4646-0849")),
    person(given = "David",family = "Rios Santini",
    role = c("ctb")),
    person(given = "Katriona",family = "Goldmann",
    role = c("ctb"),
    comment = c(ORCID = "0000-0002-9073-6323")),
    person(given = "Ryan C.", family = "Thompson", 
    role=c("ctb")))
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>
BugReports: https://github.com/myles-lewis/nestedcv/issues
URL: https://github.com/myles-lewis/nestedcv
Description: Implements nested k*l-fold cross-validation for lasso and
        elastic-net regularised linear models via the 'glmnet' package
        and other machine learning models via the 'caret' package
        <doi:10.1093/bioadv/vbad048>. Cross-validation of 'glmnet'
        alpha mixing parameter and embedded fast filter functions for
        feature selection are provided. Described as double
        cross-validation by Stone (1977)
        <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a
        method using outer CV to measure unbiased model performance
        metrics when fitting Bayesian linear and logistic regression
        shrinkage models using the horseshoe prior over parameters to
        encourage a sparse model as described by Piironen & Vehtari
        (2017) <doi:10.1214/17-EJS1337SI>.
Language: en-gb
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: caret, data.table, doParallel, foreach, future.apply, ggplot2,
        glmnet, matrixStats, matrixTests, methods, parallel, pROC,
        Rfast, RhpcBLASctl, rlang, ROCR
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Suggests: Boruta, CORElearn, fastshap (>= 0.1.0), gbm, ggbeeswarm,
        ggpubr, hsstan, mda, mlbench, pbapply, pls, randomForest,
        ranger, RcppEigen, rmarkdown, knitr, SuperLearner
VignetteBuilder: knitr
Config/pak/sysreqs: make libicu-dev
Repository: https://myles-lewis.r-universe.dev
Date/Publication: 2026-06-19 12:54:31 UTC
RemoteUrl: https://github.com/myles-lewis/nestedcv
RemoteRef: HEAD
RemoteSha: da40b29c10f1004cb74f96a0276d9ab67f658a8f
NeedsCompilation: no
Packaged: 2026-06-19 13:37:17 UTC; root
Author: Myles Lewis [aut, cre] (ORCID: <https://orcid.org/0000-0001-9365-5345>),
  Athina Spiliopoulou [aut] (ORCID:
    <https://orcid.org/0000-0002-5929-6585>),
  Cankut Cubuk [ctb] (ORCID: <https://orcid.org/0000-0003-4646-0849>),
  David Rios Santini [ctb],
  Katriona Goldmann [ctb] (ORCID:
    <https://orcid.org/0000-0002-9073-6323>),
  Ryan C. Thompson [ctb]