{ "_id": "6aad713a3d719c1f840775f5", "Package": "SVEMnet", "Type": "Package", "Title": "Self-Validated Ensemble Models with Lasso and Relaxed Elastic\nNet Regression", "Version": "3.6.2", "Date": "2026-09-18", "Authors@R": "person(given = \"Andrew T.\",\nfamily = \"Karl\",\nemail = \"akarl@asu.edu\",\nrole = c(\"cre\", \"aut\"),\ncomment = c(ORCID = \"0000-0002-5933-8706\"))", "Description": "Implements the self-validated elastic-net and relaxed\nelastic-net ensemble modeling and multi-response optimization\nworkflow described in Karl (2026)\n. Self-validated ensemble\nmodels (SVEM; Lemkus et al. (2021)\n) are fitted for\nsmall-sample design-of-experiments and related workflows using\n'glmnet' (Friedman et al. (2010) ).\nFractional random-weight bootstraps with anti-correlated\nvalidation copies are used to tune penalty paths by\nvalidation-weighted AIC/BIC. Supports Gaussian and binomial\nresponses, deterministic expansion helpers for shared factor\nspaces, prediction with bootstrap uncertainty, and a\nrandom-search optimizer that respects mixture constraints and\ncombines multiple responses via desirability functions. Also\nincludes a permutation-based whole-model test for Gaussian SVEM\nfits (Karl (2024) ).\nPackage code was drafted with assistance from generative AI\ntools.", "URL": "https://doi.org/10.1016/j.chemolab.2026.105660,\nhttps://arxiv.org/abs/2511.20968", "License": "GPL-2 | GPL-3", "Encoding": "UTF-8", "Config/testthat/edition": "3", "LazyData": "true", "Config/roxygen2/version": "8.0.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-18 17:07:13 UTC", "User": "root" }, "Author": "Andrew T. Karl [cre, aut] (ORCID:\n)", "Maintainer": "Andrew T. Karl ", "Repository": "https://akarl46556.r-universe.dev", "Date/Publication": "2026-09-18 16:33:34 UTC", "RemoteUrl": "https://github.com/cran/SVEMnet", "RemoteRef": "HEAD", "RemoteSha": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "_user": "akarl46556", "_type": "src", "_file": "SVEMnet_3.6.2.tar.gz", "_fileid": "https://r2.ropensci.org/74fac06a2598adc2fa750b426e078a39334642de55f79a886266ea2f0e251408", "_filesize": 736192, "_sha256": "74fac06a2598adc2fa750b426e078a39334642de55f79a886266ea2f0e251408", "_expires": "2026-12-27T17:13:28.000Z", "_created": "2026-09-18T17:07:13.000Z", "_published": "2026-09-18T17:13:30.628Z", "_jobs": [ { "job": 105689524030, "time": 169, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10559460354" }, { "job": 105689524077, "time": 164, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10559430382" }, { "job": 105689524072, "time": 153, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "10559310924" }, { "job": 105689523984, "time": 128, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "10557734747" }, { "job": 105688544553, "time": 182, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "10557979101" }, { "job": 105689523919, "time": 120, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "10559090563" }, { "job": 105689523973, "time": 129, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10559420305" }, { "job": 105689523908, "time": 129, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "10559385313" }, { "job": 105689524071, "time": 127, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10558849636" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272", "_status": "success", "_upstream": "https://github.com/cran/SVEMnet", "_commit": { "id": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "author": "Andrew T. Karl ", "committer": "cran-robot ", "message": "version 3.6.2\n", "time": 1789749214 }, "_maintainer": { "name": "Andrew T. Karl", "email": "akarl@asu.edu", "login": "akarl46556", "description": "", "uuid": 37884655, "orcid": "0000-0002-5933-8706" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0.0", "role": "Depends" }, { "package": "glmnet", "version": ">= 4.1-6", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "cluster", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "lhs", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "foreach", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "RhpcBLASctl", "role": "Suggests" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-39", "n": 1 }, { "week": "2025-42", "n": 1 }, { "week": "2025-45", "n": 1 }, { "week": "2025-48", "n": 2 }, { "week": "2026-04", "n": 1 }, { "week": "2026-23", "n": 1 }, { "week": "2026-27", "n": 1 }, { "week": "2026-34", "n": 1 }, { "week": "2026-36", "n": 1 }, { "week": "2026-38", "n": 1 } ], "_tags": [ { "name": "2.2.4", "date": "2025-09-26" }, { "name": "2.3.1", "date": "2025-10-14" }, { "name": "2.5.4", "date": "2025-11-09" }, { "name": "3.1.2", "date": "2025-11-24" }, { "name": "3.1.4", "date": "2025-11-28" }, { "name": "3.2.0", "date": "2026-01-23" }, { "name": "3.2.1", "date": "2026-06-02" }, { "name": "3.2.3", "date": "2026-07-02" }, { "name": "3.5.0", "date": "2026-08-20" }, { "name": "3.6.0", "date": "2026-09-06" }, { "name": "3.6.2", "date": "2026-09-18" } ], "_stars": 0, "_contributors": [ { "user": "akarl46556", "count": 18, "uuid": 37884655 } ], "_userbio": { "uuid": 37884655, "type": "user", "name": "akarl46556", "followers": 0 }, "_downloads": { "count": 383, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/SVEMnet" }, "_searchresults": 2, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/SVEMnet.html" ], "_realowner": "akarl46556", "_cranurl": false, "_releases": [ { "version": "1.0.3", "date": "2024-11-20" }, { "version": "1.1.1", "date": "2024-11-29" }, { "version": "1.2.1", "date": "2024-12-07" }, { "version": "1.3.0", "date": "2024-12-21" }, { "version": "1.4.0", "date": "2025-08-18" }, { "version": "1.5.3", "date": "2025-08-22" }, { "version": "2.1.3", "date": "2025-09-09" }, { "version": "2.2.4", "date": "2025-09-26" }, { "version": "2.3.1", "date": "2025-10-13" }, { "version": "2.5.4", "date": "2025-11-09" }, { "version": "3.1.2", "date": "2025-11-24" }, { "version": "3.1.4", "date": "2025-11-28" }, { "version": "3.2.0", "date": "2026-01-23" }, { "version": "3.2.1", "date": "2026-06-02" }, { "version": "3.2.3", "date": "2026-07-02" }, { "version": "3.5.0", "date": "2026-08-20" }, { "version": "3.6.0", "date": "2026-09-08" }, { "version": "3.6.2", "date": "2026-09-18" } ], "_exports": [ "bigexp_formula", "bigexp_prepare", "bigexp_terms", "bigexp_train", "forward_aicc", "glmnet_with_cv", "predict_cv", "svem_export_candidates_csv", "svem_forward", "svem_ij_variance", "svem_nonzero", "svem_random_table_multi", "svem_score_random", "svem_select_from_score_table", "svem_significance_test_parallel", "svem_thompson_batch", "svem_wmt_multi", "SVEMnet", "with_bigexp_contrasts" ], "_datasets": [ { "name": "lipid_screen", "title": "Lipid formulation screening data", "object": "lipid_screen", "class": [ "data.frame" ], "fields": [ "RunID", "PEG", "Helper", "Ionizable", "Cholesterol", "Ionizable_Lipid_Type", "N_P_ratio", "flow_rate", "Operator", "Potency", "Size", "PDI", "Notes" ], "rows": 23, "table": true, "tojson": true } ], "_help": [ { "page": "SVEMnet-package", "title": "SVEMnet: Self-Validated Ensemble Models with Relaxed Lasso and Elastic-Net Regression", "topics": [ "SVEMnet-package" ] }, { "page": "bigexp_formula", "title": "Construct a formula for a new response using a bigexp_spec", "topics": [ "bigexp_formula" ] }, { "page": "bigexp_prepare", "title": "Prepare data to match a 'bigexp_spec'", "topics": [ "bigexp_prepare" ] }, { "page": "bigexp_terms", "title": "Create a deterministic expansion spec for wide polynomial and interaction models", "topics": [ "bigexp_terms" ] }, { "page": "bigexp_train", "title": "Build a spec and prepare training data in one call", "topics": [ "bigexp_train" ] }, { "page": "coef.svem_model", "title": "Coefficients for SVEM Models", "topics": [ "coef.svem_model" ] }, { "page": "forward_aicc", "title": "Forward Selection by AICc (or AIC / BIC)", "topics": [ "forward_aicc" ] }, { "page": "glmnet_with_cv", "title": "Fit a glmnet Model with Repeated Cross-Validation", "topics": [ "glmnet_with_cv" ] }, { "page": "lipid_screen", "title": "Lipid formulation screening data", "topics": [ "lipid_screen" ] }, { "page": "plot.svem_binomial", "title": "Plot Method for SVEM Binomial Models", "topics": [ "plot.svem_binomial" ] }, { "page": "plot.svem_model", "title": "Plot Method for SVEM Models (Gaussian / Generic)", "topics": [ "plot.svem_model" ] }, { "page": "plot.svem_significance_test", "title": "Plot SVEM significance test results for one or more responses", "topics": [ "plot.svem_significance_test" ] }, { "page": "predict_cv", "title": "Predict from glmnet_with_cv Fits (svem_cv Objects)", "topics": [ "predict.svem_cv", "predict_cv" ] }, { "page": "predict.svem_model", "title": "Predict Method for SVEM Models (Gaussian and Binomial)", "concept": [ "SVEM methods" ], "topics": [ "predict.svem_model" ] }, { "page": "print.bigexp_formula", "title": "Print a formula that carries a 'bigexp_spec' attribute", "topics": [ "print.bigexp_formula" ] }, { "page": "print.bigexp_spec", "title": "Print method for bigexp_spec objects", "topics": [ "print.bigexp_spec" ] }, { "page": "print.svem_significance_test", "title": "Print Method for SVEM Significance Test", "topics": [ "print.svem_significance_test" ] }, { "page": "print.svem_thompson_batch", "title": "Print method for svem_thompson_batch objects", "topics": [ "print.svem_thompson_batch" ] }, { "page": "svem_export_candidates_csv", "title": "Export SVEM candidate sets to CSV", "topics": [ "svem_export_candidates_csv" ] }, { "page": "svem_forward", "title": "Fit an SVEM Model with Forward-Selection Base Learners", "topics": [ "svem_forward" ] }, { "page": "svem_ij_variance", "title": "Experimental FRW Infinitesimal-Jackknife Variance Diagnostic", "topics": [ "svem_ij_variance" ] }, { "page": "svem_nonzero", "title": "Coefficient Nonzero Percentages (SVEM)", "topics": [ "svem_nonzero" ] }, { "page": "svem_random_table_multi", "title": "Generate a Random Prediction Table from Multiple SVEMnet Models (no refit)", "topics": [ "svem_random_table_multi" ] }, { "page": "svem_score_random", "title": "Random-search scoring for SVEM models", "topics": [ "svem_score_random" ] }, { "page": "svem_select_from_score_table", "title": "Select best row and diverse candidates from an SVEM score table", "topics": [ "svem_select_from_score_table" ] }, { "page": "svem_significance_test_parallel", "title": "SVEM whole-model significance test with mixture support (parallel)", "topics": [ "svem_significance_test_parallel" ] }, { "page": "svem_thompson_batch", "title": "Propose a batch of runs by Thompson sampling from SVEM bootstrap ensembles", "topics": [ "svem_thompson_batch" ] }, { "page": "svem_wmt_multi", "title": "Whole-model tests for multiple SVEM responses (WMT wrapper)", "topics": [ "svem_wmt_multi" ] }, { "page": "SVEMnet", "title": "Fit an SVEMnet model (Self-Validated Ensemble Elastic Net)", "topics": [ "SVEMnet" ] }, { "page": "with_bigexp_contrasts", "title": "Evaluate code with the spec's recorded contrast options", "topics": [ "with_bigexp_contrasts" ] } ], "_rundeps": [ "cli", "cluster", "codetools", "cpp11", "farver", "foreach", "ggplot2", "glmnet", "glue", "gtable", "isoband", "iterators", "labeling", "lattice", "lhs", "lifecycle", "Matrix", "R6", "RColorBrewer", "Rcpp", "RcppEigen", "rlang", "S7", "scales", "shape", "survival", "vctrs", "viridisLite", "withr" ], "_score": 2, "_indexed": true, "_nocasepkg": "svemnet", "_universes": [ "akarl46556" ], "_previous": "3.6.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "3.6.2", "date": "2026-09-18T17:09:37.000Z", "distro": "resolute", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/aff6159c38a6c441b68c69029dffe74f78259f1ffc535a0eddf6125c6f897ded", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.6.1", "os": "linux", "version": "3.6.2", "date": "2026-09-18T17:09:34.000Z", "distro": "resolute", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/1ddac86af9e399f74f37b672f9554868d1c147216eb6bf51886aff764a8b13bc", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.5.3", "os": "mac", "version": "3.6.2", "date": "2026-09-18T17:11:49.000Z", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/056d3f4ca3d5e7a3ec904e68d1033f49cc0005a8b4aedada6e95f2f805a99fa0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.6.1", "os": "mac", "version": "3.6.2", "date": "2026-09-18T17:11:28.000Z", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/369b24dda1b2b2ec3cc225552e0912013e68d4a07449792d9128154bce2d9cff", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.6.0", "os": "wasm", "version": "3.6.2", "date": "2026-09-18T17:09:44.000Z", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/650b21d109703621013c405350fdb842477341d785af9e9312385c795ce05066", "status": "success", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.7.0", "os": "win", "version": "3.6.2", "date": "2026-09-18T17:08:44.000Z", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/92023f1d670c6cbff83b2a511f462c328aa64b4d1dc6d381d0cd890a35bc35de", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.5.3", "os": "win", "version": "3.6.2", "date": "2026-09-18T17:08:42.000Z", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/5116edb7d256ff608424d7e3d88fdb49f58157f38b4155d926b1b8dac70d1f50", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" }, { "r": "4.6.1", "os": "win", "version": "3.6.2", "date": "2026-09-18T17:08:43.000Z", "commit": "251c28b94033f1df0c456ac575cb9b3b76a4cfde", "fileid": "https://r2.ropensci.org/50c5b0478a842f609c1b8154ddc5a3f690e0843262c1d962afbf3dab4a5f199c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/akarl46556/actions/runs/35372156272" } ] }