{ "_id": "6a101b54acfb0bcc41c8707a", "Package": "nestedcv", "Title": "Nested Cross-Validation with 'glmnet' and 'caret'", "Version": "0.8.3", "Authors@R": "c(person(given = \"Myles\",family = \"Lewis\",\nrole = c(\"aut\", \"cre\"),\nemail = \"myles.lewis@qmul.ac.uk\",\ncomment = c(ORCID = \"0000-0001-9365-5345\")),\nperson(given = \"Athina\",family = \"Spiliopoulou\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-5929-6585\")),\nperson(given = \"Cankut\",family = \"Cubuk\",\nrole = c(\"ctb\"),\nemail = \"c.cubuk@qmul.ac.uk\",\ncomment = c(ORCID = \"0000-0003-4646-0849\")),\nperson(given = \"Katriona\",family = \"Goldmann\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0002-9073-6323\")),\nperson(given = \"Ryan C.\", family = \"Thompson\",\nrole=c(\"ctb\")))", "Maintainer": "Myles Lewis ", "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\nelastic-net regularised linear models via the 'glmnet' package\nand other machine learning models via the 'caret' package\n. Cross-validation of 'glmnet'\nalpha mixing parameter and embedded fast filter functions for\nfeature selection are provided. Described as double\ncross-validation by Stone (1977)\n. Also implemented is a\nmethod using outer CV to measure unbiased model performance\nmetrics when fitting Bayesian linear and logistic regression\nshrinkage models using the horseshoe prior over parameters to\nencourage a sparse model as described by Piironen & Vehtari\n(2017) .", "Language": "en-gb", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "make libicu-dev", "Repository": "https://myles-lewis.r-universe.dev", "Date/Publication": "2026-04-14 08:37:58 UTC", "RemoteUrl": "https://github.com/myles-lewis/nestedcv", "RemoteRef": "HEAD", "RemoteSha": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-14 09:20:32 UTC", "User": "root" }, "Author": "Myles Lewis [aut, cre] (ORCID: ),\nAthina Spiliopoulou [aut] (ORCID:\n),\nCankut Cubuk [ctb] (ORCID: ),\nKatriona Goldmann [ctb] (ORCID:\n),\nRyan C. Thompson [ctb]", "MD5sum": "431151a54dd4d37b6c1c15a64043bc88", "_user": "myles-lewis", "_type": "src", "_file": "nestedcv_0.8.3.tar.gz", "_fileid": "df7a15bb9545a2629660d8ad9b3b08b19f329dcf810759b8e15c8846b32ce6ef", "_filesize": 761671, "_sha256": "df7a15bb9545a2629660d8ad9b3b08b19f329dcf810759b8e15c8846b32ce6ef", "_created": "2026-05-14T09:20:32.000Z", "_published": "2026-05-22T09:01:08.071Z", "_distro": "noble", "_jobs": [ { "job": 77348350812, "time": 230, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "ERROR", "artifact": "6991260891" }, { "job": 77348350550, "time": 238, "config": "linux-release-x86_64", "r": "4.6.0", "check": "ERROR", "artifact": "6991262581" }, { "job": 77348350553, "time": 145, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "ERROR", "artifact": "6991236584" }, { "job": 77348350675, "time": 149, "config": "macos-release-arm64", "r": "4.6.0", "check": "ERROR", "artifact": "6991237674" }, { "job": 77348349953, "time": 315, "config": "source", "r": "4.6.0", "check": "ERROR", "artifact": "6991195702" }, { "job": 77348349852, "time": 160, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7156731152" }, { "job": 77348350717, "time": 188, "config": "windows-devel", "r": "4.7.0", "check": "ERROR", "artifact": "6991248780" }, { "job": 77348350600, "time": 207, "config": "windows-oldrel", "r": "4.5.3", "check": "ERROR", "artifact": "6991254215" }, { "job": 77348350777, "time": 170, "config": "windows-release", "r": "4.6.0", "check": "ERROR", "artifact": "6991243446" } ], "_buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654", "_status": "failure", "_host": "GitHub-Actions", "_upstream": "https://github.com/myles-lewis/nestedcv", "_commit": { "id": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "author": "Myles Lewis ", "committer": "GitHub ", "message": "Merge pull request #47 from RLau0/axis_ticks_aes\n\naxis ticks aesthetics", "time": 1776155878 }, "_maintainer": { "name": "Myles Lewis", "email": "myles.lewis@qmul.ac.uk", "login": "myles-lewis", "uuid": 24961656, "orcid": "0000-0001-9365-5345" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "caret", "role": "Imports" }, { "package": "data.table", "role": "Imports" }, { "package": "doParallel", "role": "Imports" }, { "package": "foreach", "role": "Imports" }, { "package": "future.apply", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "glmnet", "role": "Imports" }, { "package": "matrixStats", "role": "Imports" }, { "package": "matrixTests", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "pROC", "role": "Imports" }, { "package": "Rfast", "role": "Imports" }, { "package": "RhpcBLASctl", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "ROCR", "role": "Imports" }, { "package": "Boruta", "role": "Suggests" }, { "package": "CORElearn", "role": "Suggests" }, { "package": "fastshap", "version": ">= 0.1.0", "role": "Suggests" }, { "package": "gbm", "role": "Suggests" }, { "package": "ggbeeswarm", "role": "Suggests" }, { "package": "ggpubr", "role": "Suggests" }, { "package": "hsstan", "role": "Suggests" }, { "package": "mda", "role": "Suggests" }, { "package": "mlbench", "role": "Suggests" }, { "package": "pbapply", "role": "Suggests" }, { "package": "pls", "role": "Suggests" }, { "package": "randomForest", "role": "Suggests" }, { "package": "ranger", "role": "Suggests" }, { "package": "RcppEigen", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "SuperLearner", "role": "Suggests" } ], "_owner": "myles-lewis", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-39", "n": 1 }, { "week": "2026-12", "n": 1 }, { "week": "2026-15", "n": 7 }, { "week": "2026-16", "n": 2 } ], "_tags": [], "_stars": 17, "_contributors": [ { "user": "myles-lewis", "count": 992, "uuid": 24961656 }, { "user": "aspiliop", "count": 5, "uuid": 69569374 }, { "user": "rlau0", "count": 2, "uuid": 102387811 }, { "user": "elisabettasciacca", "count": 2, "uuid": 70027703 }, { "user": "cankutcubuk", "count": 1, "uuid": 17905535 } ], "_userbio": { "uuid": 24961656, "type": "user", "name": "Myles Lewis" }, "_downloads": { "count": 1015, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/nestedcv" }, "_devurl": "https://github.com/myles-lewis/nestedcv", "_searchresults": 68, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/nestedcv.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/myles-lewis/nestedcv", "_realowner": "myles-lewis", "_cranurl": true, "_releases": [ { "version": "0.2.3", "date": "2022-07-07" }, { "version": "0.3.0", "date": "2022-09-10" }, { "version": "0.4.0", "date": "2022-10-23" }, { "version": "0.4.4", "date": "2022-12-05" }, { "version": "0.6.1", "date": "2023-04-16" }, { "version": "0.6.2", "date": "2023-05-15" }, { "version": "0.6.4", "date": "2023-05-30" }, { "version": "0.6.6", "date": "2023-06-08" }, { "version": "0.6.7", "date": "2023-07-02" }, { "version": "0.6.9", "date": "2023-08-24" }, { "version": "0.7.0", "date": "2023-10-26" }, { "version": "0.7.3", "date": "2023-12-04" }, { "version": "0.7.4", "date": "2024-01-30" }, { "version": "0.7.8", "date": "2024-03-13" }, { "version": "0.7.9", "date": "2024-07-04" }, { "version": "0.7.10", "date": "2024-08-16" }, { "version": "0.7.12", "date": "2024-11-27" }, { "version": "0.8.0", "date": "2025-03-10" }, { "version": "0.8.2", "date": "2026-04-10" } ], "_exports": [ "anova_filter", "barplot_var_stability", "bin_stat_filter", "boot_anova", "boot_correl", "boot_filter", "boot_lm", "boot_ttest", "boot_wilcoxon", "boruta_filter", "boxplot_expression", "class_balance", "class_stat_filter", "collinear", "combo_filter", "cor_stat_filter", "correl_filter", "correls2", "cv_coef", "cv_varImp", "cva.glmnet", "glmnet_coefs", "glmnet_filter", "hist_var_ranks", "innercv_preds", "innercv_roc", "innercv_summary", "lm_filter", "mcc", "mcc_multi", "metrics", "model.hsstan", "nestcv.glmnet", "nestcv.SuperLearner", "nestcv.train", "one_hot", "outercv", "plot_alphas", "plot_caret", "plot_lambdas", "plot_shap_bar", "plot_shap_beeswarm", "plot_var_ranks", "plot_var_stability", "plot_varImp", "pls_filter", "prc", "pred_nestcv_glmnet", "pred_nestcv_glmnet_class", "pred_SuperLearner", "pred_train", "pred_train_class", "predSummary", "randomsample", "ranger_filter", "relieff_filter", "repeatcv", "repeatfolds", "rf_filter", "slim", "smote", "stat_filter", "summary_vars", "supervisedPCA", "train_preds", "train_roc", "train_summary", "ttest_filter", "txtProgressBar2", "var_direction", "var_stability", "weight", "wilcoxon_filter" ], "_help": [ { "page": "barplot_var_stability", "title": "Barplot variable stability", "topics": [ "barplot_var_stability" ] }, { "page": "boot_filter", "title": "Bootstrap for filter functions", "topics": [ "boot_filter" ] }, { "page": "boot_ttest", "title": "Bootstrap univariate filters", "topics": [ "boot_anova", "boot_correl", "boot_lm", "boot_ttest", "boot_wilcoxon" ] }, { "page": "boruta_filter", "title": "Boruta filter", "topics": [ "boruta_filter" ] }, { "page": "boxplot_expression", "title": "Boxplot expression levels of model predictors", "topics": [ "boxplot_expression" ] }, { "page": "class_balance", "title": "Check class balance in training folds", "topics": [ "class_balance", "class_balance.default", "class_balance.nestcv.train" ] }, { "page": "coef.cva.glmnet", "title": "Extract coefficients from a cva.glmnet object", "topics": [ "coef.cva.glmnet" ] }, { "page": "coef.nestcv.glmnet", "title": "Extract coefficients from nestcv.glmnet object", "topics": [ "coef.nestcv.glmnet" ] }, { "page": "collinear", "title": "Filter to reduce collinearity in predictors", "topics": [ "collinear" ] }, { "page": "combo_filter", "title": "Combo filter", "topics": [ "combo_filter" ] }, { "page": "correls2", "title": "Correlation between a vector and a matrix", "topics": [ "correls2" ] }, { "page": "cv_coef", "title": "Coefficients from outer CV glmnet models", "topics": [ "cv_coef" ] }, { "page": "cv_varImp", "title": "Extract variable importance from outer CV caret models", "topics": [ "cv_varImp" ] }, { "page": "cva.glmnet", "title": "Cross-validation of alpha for glmnet", "topics": [ "cva.glmnet" ] }, { "page": "glmnet_coefs", "title": "glmnet coefficients", "topics": [ "glmnet_coefs" ] }, { "page": "glmnet_filter", "title": "glmnet filter", "topics": [ "glmnet_filter" ] }, { "page": "innercv_preds", "title": "Inner CV predictions", "topics": [ "innercv_preds", "innercv_preds.nestcv.glmnet", "innercv_preds.nestcv.train" ] }, { "page": "innercv_roc", "title": "Build ROC curve from left-out folds from inner CV", "topics": [ "innercv_roc" ] }, { "page": "innercv_summary", "title": "Summarise performance on inner CV test folds", "topics": [ "innercv_summary" ] }, { "page": "lines.prc", "title": "Add precision-recall curve to a plot", "topics": [ "lines.prc" ] }, { "page": "lm_filter", "title": "Linear model filter", "topics": [ "lm_filter" ] }, { "page": "mcc", "title": "Matthews correlation coefficient", "topics": [ "mcc", "mcc_multi" ] }, { "page": "metrics", "title": "Model performance metrics", "topics": [ "metrics" ] }, { "page": "model.hsstan", "title": "hsstan model for cross-validation", "topics": [ "model.hsstan" ] }, { "page": "nestcv.glmnet", "title": "Nested cross-validation with glmnet", "topics": [ "nestcv.glmnet" ] }, { "page": "nestcv.SuperLearner", "title": "Outer cross-validation of SuperLearner model", "topics": [ "nestcv.SuperLearner" ] }, { "page": "nestcv.train", "title": "Nested cross-validation for caret", "topics": [ "nestcv.train" ] }, { "page": "one_hot", "title": "One-hot encode", "topics": [ "one_hot" ] }, { "page": "outercv", "title": "Outer cross-validation of selected models", "topics": [ "outercv", "outercv.default", "outercv.formula" ] }, { "page": "plot_alphas", "title": "Plot cross-validated glmnet alpha", "topics": [ "plot_alphas" ] }, { "page": "plot_caret", "title": "Plot caret tuning", "topics": [ "plot_caret" ] }, { "page": "plot_lambdas", "title": "Plot cross-validated glmnet lambdas across outer folds", "topics": [ "plot_lambdas" ] }, { "page": "plot_shap_bar", "title": "SHAP importance bar plot", "topics": [ "plot_shap_bar" ] }, { "page": "plot_shap_beeswarm", "title": "SHAP importance beeswarm plot", "topics": [ "plot_shap_beeswarm" ] }, { "page": "plot_var_ranks", "title": "Plot variable importance rankings", "topics": [ "hist_var_ranks", "plot_var_ranks" ] }, { "page": "plot_var_stability", "title": "Plot variable stability", "topics": [ "plot_var_stability" ] }, { "page": "plot_varImp", "title": "Variable importance plot", "topics": [ "plot_varImp" ] }, { "page": "plot.cva.glmnet", "title": "Plot lambda across range of alphas", "topics": [ "plot.cva.glmnet" ] }, { "page": "plot.prc", "title": "Plot precision-recall curve", "topics": [ "plot.prc" ] }, { "page": "pls_filter", "title": "Partial Least Squares filter", "topics": [ "pls_filter" ] }, { "page": "prc", "title": "Build precision-recall curve", "topics": [ "prc", "prc.data.frame", "prc.default", "prc.nestcv.glmnet", "prc.nestcv.SuperLearner", "prc.nestcv.train", "prc.outercv", "prc.repeatcv" ] }, { "page": "pred_nestcv_glmnet", "title": "Prediction wrappers to use fastshap with nestedcv", "topics": [ "pred_nestcv_glmnet", "pred_nestcv_glmnet_class", "pred_SuperLearner", "pred_train", "pred_train_class" ] }, { "page": "predict.cva.glmnet", "title": "Predict method for cva.glmnet models", "topics": [ "predict.cva.glmnet" ] }, { "page": "predict.hsstan", "title": "Predict from hsstan model fitted within cross-validation", "topics": [ "predict.hsstan" ] }, { "page": "predict.nestcv.glmnet", "title": "Predict method for nestcv.glmnet fits", "topics": [ "predict.nestcv.glmnet" ] }, { "page": "predSummary", "title": "Summarise prediction performance metrics", "topics": [ "predSummary" ] }, { "page": "randomsample", "title": "Oversampling and undersampling", "topics": [ "randomsample" ] }, { "page": "ranger_filter", "title": "Random forest ranger filter", "topics": [ "ranger_filter" ] }, { "page": "relieff_filter", "title": "ReliefF filter", "topics": [ "relieff_filter" ] }, { "page": "repeatcv", "title": "Repeated nested CV", "topics": [ "repeatcv" ] }, { "page": "repeatfolds", "title": "Create folds for repeated nested CV", "topics": [ "repeatfolds" ] }, { "page": "rf_filter", "title": "Random forest filter", "topics": [ "rf_filter" ] }, { "page": "slim", "title": "Slim nestedcv models", "topics": [ "slim" ] }, { "page": "smote", "title": "SMOTE", "topics": [ "smote" ] }, { "page": "stat_filter", "title": "Univariate filter for binary classification with mixed predictor datatypes", "topics": [ "bin_stat_filter", "class_stat_filter", "cor_stat_filter", "stat_filter" ] }, { "page": "summary_vars", "title": "Summarise variables", "topics": [ "summary_vars" ] }, { "page": "supervisedPCA", "title": "Supervised PCA plot", "topics": [ "supervisedPCA" ] }, { "page": "train_preds", "title": "Outer training fold predictions", "topics": [ "train_preds" ] }, { "page": "train_roc", "title": "Build ROC curve from outer CV training folds", "topics": [ "train_roc" ] }, { "page": "train_summary", "title": "Summarise performance on outer training folds", "topics": [ "train_summary" ] }, { "page": "ttest_filter", "title": "Univariate filters", "topics": [ "anova_filter", "correl_filter", "ttest_filter", "wilcoxon_filter" ] }, { "page": "txtProgressBar2", "title": "Text Progress Bar 2", "topics": [ "txtProgressBar2" ] }, { "page": "var_direction", "title": "Variable directionality", "topics": [ "var_direction" ] }, { "page": "var_stability", "title": "Variable stability", "topics": [ "var_stability", "var_stability.nestcv.glmnet", "var_stability.nestcv.train", "var_stability.repeatcv" ] }, { "page": "weight", "title": "Calculate weights for class imbalance", "topics": [ "weight" ] } ], "_readme": "https://github.com/myles-lewis/nestedcv/raw/HEAD/README.md", "_rundeps": [ "bitops", "caret", "caTools", "class", "cli", "clock", "codetools", "cpp11", "data.table", "diagram", "digest", "doParallel", "dplyr", "e1071", "farver", "foreach", "future", "future.apply", "generics", "ggplot2", "glmnet", "globals", "glue", "gower", "gplots", "gtable", "gtools", "hardhat", "ipred", "isoband", "iterators", "KernSmooth", "labeling", "lattice", "lava", "lifecycle", "listenv", "lubridate", "magrittr", "MASS", "Matrix", "matrixStats", "matrixTests", "ModelMetrics", "nlme", "nnet", "numDeriv", "parallelly", "pillar", "pkgconfig", "plyr", "pROC", "prodlim", "progressr", "proxy", "purrr", "R6", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "RcppParallel", "recipes", "reshape2", "Rfast", "RhpcBLASctl", "rlang", "ROCR", "rpart", "S7", "scales", "shape", "sparsevctrs", "SQUAREM", "stringi", "stringr", "survival", "tibble", "tidyr", "tidyselect", "timechange", "timeDate", "tzdb", "utf8", "vctrs", "viridisLite", "withr", "zigg" ], "_score": 5.972513863325685, "_indexed": true, "_nocasepkg": "nestedcv", "_universes": [ "myles-lewis" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.8.3", "date": "2026-05-14T09:23:45.000Z", "distro": "noble", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "16a99f1dcb7005345d2b56071ca6e14376898ddb110a9bf90c5c7e8893422b43", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.6.0", "os": "linux", "version": "0.8.3", "date": "2026-05-14T09:23:51.000Z", "distro": "noble", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "115134cbfc069010e4be320c11c2a9eb5f365cba5d63cb390a3599569d9c4ab0", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.5.3", "os": "mac", "version": "0.8.3", "date": "2026-05-14T09:22:38.000Z", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "f2b8892eef07a0797924bd996b3b64066b86ee4a6f9f932a42c82da4c635804d", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.6.0", "os": "mac", "version": "0.8.3", "date": "2026-05-14T09:22:40.000Z", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "2e41181e7789f4ff85481afe0119bb02b0f0878e35979e8f51ef74ccde5dd9d4", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.7.0", "os": "win", "version": "0.8.3", "date": "2026-05-14T09:22:56.000Z", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "c119cbd273ce69fea6e3c31c30c95725b0a278b89257e23b375f070710e6cf57", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.5.3", "os": "win", "version": "0.8.3", "date": "2026-05-14T09:23:01.000Z", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "cff6e15ca821d30fc4b883e81465ce5b6beea0912e56b77e3f491c208cd0ae9c", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.6.0", "os": "win", "version": "0.8.3", "date": "2026-05-14T09:22:38.000Z", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "18541cc1059f59f0ade283d95c7e7536ece382aa1ff3ff2bc2c92214a8592258", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" }, { "r": "4.6.0", "os": "wasm", "version": "0.8.3", "date": "2026-05-22T09:00:08.000Z", "commit": "6d701c0b4dbe1ac9d8e95d5ca913fef65a2ec436", "fileid": "df9e7add8c81b0c9682a8ab83540e5194d107048ca6bc0ec186a14037a85e28d", "status": "success", "buildurl": "https://github.com/r-universe/myles-lewis/actions/runs/25852070654" } ] }