{ "_id": "6a117156acfb0bcc41cf737a", "Package": "SelectBoost", "Type": "Package", "Title": "A General Algorithm to Enhance the Performance of Variable\nSelection Methods in Correlated Datasets", "Version": "2.3.0", "Date": "2025-09-10", "biocViews": "", "Authors@R": "c(\nperson(given = \"Frederic\", family= \"Bertrand\", role = c(\"cre\", \"aut\"), email = \"frederic.bertrand@lecnam.net\", comment = c(ORCID = \"0000-0002-0837-8281\")),\nperson(given = \"Myriam\", family= \"Maumy-Bertrand\", role = c(\"aut\"), email = \"myriam.maumy@ehesp.fr\", comment = c(ORCID = \"0000-0002-4615-1512\")),\nperson(given = \"Ismail\", family= \"Aouadi\", role = c(\"ctb\"), email = \"i.aouadi@unistra.fr\"),\nperson(given = \"Nicolas\", family= \"Jung\", role = c(\"ctb\"), email = \"nicolas.jung@unistra.fr\"))", "Author": "Frederic Bertrand [cre, aut]\n(), Myriam\nMaumy-Bertrand [aut] (),\nIsmail Aouadi [ctb], Nicolas Jung [ctb]", "Maintainer": "Frederic Bertrand ", "Description": "An implementation of the selectboost algorithm (Bertrand\net al. 2020, 'Bioinformatics',\n), which is a general\nalgorithm that improves the precision of any existing variable\nselection method. This algorithm is based on highly intensive\nsimulations and takes into account the correlation structure of\nthe data. It can either produce a confidence index for variable\nselection or it can be used in an experimental design planning\nperspective.", "License": "GPL-3", "Encoding": "UTF-8", "Classification/MSC": "62H11, 62J12, 62J99", "LazyData": "true", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.2", "URL": "https://fbertran.github.io/SelectBoost/,\nhttps://github.com/fbertran/SelectBoost/", "BugReports": "https://github.com/fbertran/SelectBoost/issues/", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libglpk-dev make libmagick++-dev gsfonts texlive\nlibjpeg-dev libpng-dev libxml2-dev libssl-dev", "Repository": "https://fbertran.r-universe.dev", "Date/Publication": "2025-09-24 09:55:09 UTC", "RemoteUrl": "https://github.com/fbertran/selectboost", "RemoteRef": "HEAD", "RemoteSha": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-23 09:15:41 UTC", "User": "root" }, "MD5sum": "e7106e9ed75c974f94bde209bc065cc4", "_user": "fbertran", "_type": "src", "_file": "SelectBoost_2.3.0.tar.gz", "_fileid": "6ba90905b1383d7830fa92ae7d99bf26ea5cea075910ccb1aa3b76f65ba0fc06", "_filesize": 1194565, "_sha256": "6ba90905b1383d7830fa92ae7d99bf26ea5cea075910ccb1aa3b76f65ba0fc06", "_created": "2026-05-23T09:15:41.000Z", "_published": "2026-05-23T09:20:22.412Z", "_distro": "noble", "_jobs": [ { "job": 77511783694, "time": 239, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "WARNING", "artifact": "7175909742" }, { "job": 77511783695, "time": 241, "config": "linux-release-x86_64", "r": "4.6.0", "check": "WARNING", "artifact": "7175909842" }, { "job": 77511783726, "time": 102, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "WARNING", "artifact": "7175903996" }, { "job": 77511783690, "time": 111, "config": "macos-release-arm64", "r": "4.6.0", "check": "WARNING", "artifact": "7175903992" }, { "job": 77511549294, "time": 287, "config": "source", "r": "4.6.0", "check": "ERROR", "artifact": "7175888585" }, { "job": 77511783680, "time": 181, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7175904638" }, { "job": 77511783727, "time": 178, "config": "windows-devel", "r": "4.7.0", "check": "WARNING", "artifact": "7175904439" }, { "job": 77511783724, "time": 140, "config": "windows-oldrel", "r": "4.5.3", "check": "WARNING", "artifact": "7175900971" }, { "job": 77511783710, "time": 150, "config": "windows-release", "r": "4.6.0", "check": "WARNING", "artifact": "7175902026" } ], "_buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137", "_status": "failure", "_host": "GitHub-Actions", "_upstream": "https://github.com/fbertran/selectboost", "_commit": { "id": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "author": "Frederic Bertrand ", "committer": "Frederic Bertrand ", "message": "chore: ignore .DS_Store (git & R build)\n", "time": 1758707709 }, "_maintainer": { "name": "Frederic Bertrand", "email": "frederic.bertrand@lecnam.net", "login": "fbertran", "orcid": "0000-0002-0837-8281", "twitter": "@BertrandFrdric2", "description": "Full professor in statistical modelling and data science at the CNAM Paris, France", "uuid": 6714333 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5", "role": "Depends" }, { "package": "lars", "role": "Imports" }, { "package": "glmnet", "role": "Imports" }, { "package": "igraph", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "msgps", "role": "Imports" }, { "package": "Rfast", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "Cascade", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "grDevices", "role": "Imports" }, { "package": "varbvs", "role": "Imports" }, { "package": "spls", "role": "Imports" }, { "package": "abind", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "markdown", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "mixOmics", "role": "Suggests" }, { "package": "CascadeData", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "fbertran", "_selfowned": true, "_usedby": 3, "_updates": [ { "week": "2025-37", "n": 1 }, { "week": "2025-38", "n": 1 }, { "week": "2025-39", "n": 1 } ], "_tags": [], "_topics": [ "confidence", "correlation", "correlation-structure", "modelling", "precision", "recall", "selection-algorithm" ], "_stars": 7, "_contributors": [ { "user": "fbertran", "count": 53, "uuid": 6714333 } ], "_userbio": { "uuid": 6714333, "type": "user", "name": "Frederic Bertrand", "description": "Full professor in statistical modelling and data science at the CNAM Paris, France" }, "_downloads": { "count": 648, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/SelectBoost" }, "_devurl": "https://github.com/fbertran/selectboost", "_pkgdown": "https://fbertran.github.io/SelectBoost/", "_searchresults": 12, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/SelectBoost.html", "manual.pdf" ], "_homeurl": "https://github.com/fbertran/selectboost", "_realowner": "fbertran", "_cranurl": true, "_releases": [ { "version": "1.4.0", "date": "2019-05-27" }, { "version": "2.0.0", "date": "2020-02-23" }, { "version": "2.2.0", "date": "2021-03-20" }, { "version": "2.2.1", "date": "2022-11-29" }, { "version": "2.2.2", "date": "2022-11-30" }, { "version": "2.3.0", "date": "2025-09-14" } ], "_exports": [ "AICc_glmnetB", "alasso_enet_msgps_all", "alasso_msgps_all", "auto.analyze", "autoboost", "BIC_glmnetB", "boost.adjust", "boost.apply", "boost.compcorrs", "boost.correlation_sign", "boost.findgroups", "boost.normalize", "boost.random", "boost.select", "boost.Xpass", "compsim", "enet_msgps_all", "enetf_msgps_AICc", "enetf_msgps_BIC", "enetf_msgps_Cp", "enetf_msgps_GCV", "fastboost", "force.non.inc", "group_func_1", "group_func_2", "lasso_cascade", "lasso_cv_glmnet_1se", "lasso_cv_glmnet_1se_weighted", "lasso_cv_glmnet_all_5f", "lasso_cv_glmnet_bin_1se", "lasso_cv_glmnet_bin_all", "lasso_cv_glmnet_bin_min", "lasso_cv_glmnet_min", "lasso_cv_glmnet_min_weighted", "lasso_cv_lars_1se", "lasso_cv_lars_min", "lasso_glmnet_bin_AICc", "lasso_glmnet_bin_all", "lasso_glmnet_bin_BIC", "lasso_msgps_AICc", "lasso_msgps_all", "lasso_msgps_BIC", "lasso_msgps_Cp", "lasso_msgps_GCV", "plot", "rerr", "ridge_logistic", "selectboost", "sgpls_spls_all", "simulation_cor", "simulation_DATA", "simulation_X", "spls_spls_all", "splsda_spls_all", "trajC0", "varbvs_binomial_all", "varbvs_linear_all" ], "_datasets": [ { "name": "autoboost.res.x", "title": "Autoboost lasso diabetes first order.", "object": "autoboost.res.x", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" ], "rows": 13, "table": false, "tojson": false }, { "name": "autoboost.res.x.adapt", "title": "Autoboost adaptative lasso diabetes first order.", "object": "autoboost.res.x.adapt", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" ], "rows": 13, "table": false, "tojson": false }, { "name": "autoboost.res.x2", "title": "Autoboost lasso diabetes second order.", "object": "autoboost.res.x2", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", "64" ], "rows": 13, "table": false, "tojson": false }, { "name": "autoboost.res.x2.adapt", "title": "Autoboost adaptative lasso diabetes second order.", "object": "autoboost.res.x2.adapt", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", "64" ], "rows": 13, "table": false, "tojson": false }, { "name": "F_score_C", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PB", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PB_075_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PB_095_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PB_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PL", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PL2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PL2_tW", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PL2_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PSel", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PSel_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PSel.5", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PSel.5.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_PSel.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "F_score_robust", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "fastboost.res.x", "title": "Fastboost lasso diabetes first order.", "object": "fastboost.res.x", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" ], "rows": 13, "table": false, "tojson": false }, { "name": "fastboost.res.x.adapt", "title": "Fastboost adaptative lasso diabetes first order.", "object": "fastboost.res.x.adapt", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" ], "rows": 13, "table": false, "tojson": false }, { "name": "fastboost.res.x2", "title": "Fastboost lasso diabetes second order.", "object": "fastboost.res.x2", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", "64" ], "rows": 13, "table": false, "tojson": false }, { "name": "fastboost.res.x2.adapt", "title": "Fastboost adaptative lasso diabetes second order.", "object": "fastboost.res.x2.adapt", "class": [ "selectboost" ], "fields": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", "64" ], "rows": 13, "table": false, "tojson": false }, { "name": "M", "title": "Simulated Cascade network and inference", "object": "Cascade_example", "class": [ "micro_array" ], "fields": [], "table": false, "tojson": false }, { "name": "Net", "title": "Simulated Cascade network and inference", "object": "Cascade_example", "class": [ "network" ], "fields": [], "table": false, "tojson": false }, { "name": "net_confidence", "title": "Confidence indices", "object": "Cascade_confidence", "class": [ "network.confidence" ], "fields": [], "table": false, "tojson": false }, { "name": "net_confidence_.5", "title": "Confidence indices", "object": "Cascade_confidence", "class": [ "network.confidence" ], "fields": [], "table": false, "tojson": false }, { "name": "net_confidence_thr", "title": "Confidence indices", "object": "Cascade_confidence", "class": [ "network.confidence" ], "fields": [], "table": false, "tojson": false }, { "name": "Net_inf_C", "title": "Simulated Cascade network and inference", "object": "Cascade_example", "class": [ "network" ], "fields": [], "table": false, "tojson": false }, { "name": "nv_C", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PB", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PB_075_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PB_095_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PB_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PL", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PL2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PL2_tW", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PL2_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PSel", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PSel_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PSel.5", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PSel.5.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_PSel.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "nv_robust", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "predictive_positive_value_C", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PB", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PB_075_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PB_095_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PB_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PL", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PL2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PL2_tW", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PL2_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PSel", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PSel_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PSel.5", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PSel.5.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_PSel.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "predictive_positive_value_robust", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_C", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PB", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PB_075_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PB_095_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PB_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PL", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PL2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PL2_tW", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PL2_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PSel", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PSel_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PSel.5", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PSel.5.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_PSel.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "sensitivity_robust", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_C", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PB", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PB_075_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PB_095_075", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PB_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PL", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PL2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PL2_tW", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PL2_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PSel", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PSel_W", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PSel.5", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PSel.5.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_PSel.e2", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true }, { "name": "test.seq_robust", "title": "Simulations for reverse-engineering", "object": "results_simuls_reverse_engineering_v3", "class": [ "matrix", "array" ], "fields": {}, "rows": 100, "table": true, "tojson": true } ], "_help": [ { "page": "AICc_BIC_glmnetB", "title": "AICc and BIC for glmnet logistic models", "topics": [ "AICc_BIC_glmnetB", "AICc_glmnetB", "BIC_glmnetB", "rerr", "ridge_logistic" ] }, { "page": "auto.analyze", "title": "Find limits for selectboost analysis", "concept": [ "Selectboost analyze functions" ], "topics": [ "auto.analyze", "auto.analyze.selectboost" ] }, { "page": "autoboost", "title": "Autoboost", "concept": [ "Selectboost functions" ], "topics": [ "autoboost" ] }, { "page": "autoboost.res.x", "title": "Autoboost lasso diabetes first order.", "topics": [ "autoboost.res.x" ] }, { "page": "autoboost.res.x.adapt", "title": "Autoboost adaptative lasso diabetes first order.", "topics": [ "autoboost.res.x.adapt" ] }, { "page": "autoboost.res.x2", "title": "Autoboost lasso diabetes second order.", "topics": [ "autoboost.res.x2" ] }, { "page": "autoboost.res.x2.adapt", "title": "Autoboost adaptative lasso diabetes second order.", "topics": [ "autoboost.res.x2.adapt" ] }, { "page": "boost", "title": "Boost step by step functions", "concept": [ "Selectboost functions" ], "topics": [ "boost", "boost.adjust", "boost.apply", "boost.compcorrs", "boost.correlation_sign", "boost.findgroups", "boost.normalize", "boost.random", "boost.select", "boost.Xpass" ] }, { "page": "Cascade_confidence", "title": "Confidence indices", "topics": [ "Cascade_confidence", "net_confidence", "net_confidence_.5", "net_confidence_thr" ] }, { "page": "Cascade_example", "title": "Simulated Cascade network and inference", "topics": [ "Cascade_example", "M", "Net", "Net_inf_C" ] }, { "page": "fastboost", "title": "Fastboost", "concept": [ "Selectboost functions" ], "topics": [ "fastboost" ] }, { "page": "fastboost.res.x", "title": "Fastboost lasso diabetes first order.", "topics": [ "fastboost.res.x" ] }, { "page": "fastboost.res.x.adapt", "title": "Fastboost adaptative lasso diabetes first order.", "topics": [ "fastboost.res.x.adapt" ] }, { "page": "fastboost.res.x2", "title": "Fastboost lasso diabetes second order.", "topics": [ "fastboost.res.x2" ] }, { "page": "fastboost.res.x2.adapt", "title": "Fastboost adaptative lasso diabetes second order.", "topics": [ "fastboost.res.x2.adapt" ] }, { "page": "force.non.inc", "title": "Non increasing post processinng step for selectboost analysis", "concept": [ "Selectboost analyse functions" ], "topics": [ "force.non.inc" ] }, { "page": "group_func_1", "title": "Generate groups by thresholding.", "topics": [ "group_func_1" ] }, { "page": "group_func_2", "title": "Generate groups using community analysis.", "topics": [ "group_func_2" ] }, { "page": "miscplot", "title": "Miscellaneous plot functions", "concept": [ "Plot functions" ], "topics": [ "miscplot", "plot.matrix" ] }, { "page": "network.confidence-class", "title": "Network confidence class.", "topics": [ "network.confidence-class" ] }, { "page": "plot_selectboost_cascade", "title": "plot_Selectboost_cascade", "concept": [ "Selectboost functions" ], "topics": [ "plot,network.confidence,ANY-method", "plot,network.confidence,network.confidence-method", "plot_selectboost_cascade" ] }, { "page": "plot.selectboost", "title": "Plot selectboost object", "concept": [ "Selectboost analyse functions" ], "topics": [ "plot.selectboost" ] }, { "page": "plot.summary.selectboost", "title": "Plot a summary of selectboost results", "concept": [ "Selectboost analyze functions" ], "topics": [ "plot.summary.selectboost" ] }, { "page": "reverse", "title": "Simulations for reverse-engineering", "topics": [ "F_score_C", "F_score_PB", "F_score_PB_075_075", "F_score_PB_095_075", "F_score_PB_W", "F_score_PL", "F_score_PL2", "F_score_PL2_tW", "F_score_PL2_W", "F_score_PSel", "F_score_PSel.5", "F_score_PSel.5.e2", "F_score_PSel.e2", "F_score_PSel_W", "F_score_robust", "nv_C", "nv_PB", "nv_PB_075_075", "nv_PB_095_075", "nv_PB_W", "nv_PL", "nv_PL2", "nv_PL2_tW", "nv_PL2_W", "nv_PSel", "nv_PSel.5", "nv_PSel.5.e2", "nv_PSel.e2", "nv_PSel_W", "nv_robust", "predictive_positive_value_C", "predictive_positive_value_PB", "predictive_positive_value_PB_075_075", "predictive_positive_value_PB_095_075", "predictive_positive_value_PB_W", "predictive_positive_value_PL", "predictive_positive_value_PL2", "predictive_positive_value_PL2_tW", "predictive_positive_value_PL2_W", "predictive_positive_value_PSel", "predictive_positive_value_PSel.5", "predictive_positive_value_PSel.5.e2", "predictive_positive_value_PSel.e2", "predictive_positive_value_PSel_W", "predictive_positive_value_robust", "results_simuls_reverse_engineering_v3", "sensitivity_C", "sensitivity_PB", "sensitivity_PB_075_075", "sensitivity_PB_095_075", "sensitivity_PB_W", "sensitivity_PL", "sensitivity_PL2", "sensitivity_PL2_tW", "sensitivity_PL2_W", "sensitivity_PSel", "sensitivity_PSel.5", "sensitivity_PSel.5.e2", "sensitivity_PSel.e2", "sensitivity_PSel_W", "sensitivity_robust", "test.seq_C", "test.seq_PB", "test.seq_PB_075_075", "test.seq_PB_095_075", "test.seq_PB_W", "test.seq_PL", "test.seq_PL2", "test.seq_PL2_tW", "test.seq_PL2_W", "test.seq_PSel", "test.seq_PSel.5", "test.seq_PSel.5.e2", "test.seq_PSel.e2", "test.seq_PSel_W", "test.seq_robust" ] }, { "page": "selectboost_cascade", "title": "Selectboost_cascade", "concept": [ "Selectboost functions" ], "topics": [ "selectboost", "selectboost,micro_array,micro_array-method", "selectboost,micro_array-method", "selectboost_cascade" ] }, { "page": "simulation", "title": "Miscellaneous simulation functions", "concept": [ "Simulation functions" ], "topics": [ "compsim", "compsim.simuls", "simulation", "simulation_cor", "simulation_DATA", "simulation_X" ] }, { "page": "summary.selectboost", "title": "Summarize a selectboost analysis", "concept": [ "Selectboost analyse functions" ], "topics": [ "summary.selectboost" ] }, { "page": "trajC0", "title": "Plot trajectories", "concept": [ "Selectboost analyze functions" ], "topics": [ "trajC0", "trajC0.selectboost" ] }, { "page": "var_select", "title": "Variable selection functions", "concept": [ "Variable selection functions" ], "topics": [ "enetf_msgps_AICc", "enetf_msgps_BIC", "enetf_msgps_Cp", "enetf_msgps_GCV", "lasso_cascade", "lasso_cv_glmnet_1se", "lasso_cv_glmnet_1se_weighted", "lasso_cv_glmnet_bin_1se", "lasso_cv_glmnet_bin_min", "lasso_cv_glmnet_min", "lasso_cv_glmnet_min_weighted", "lasso_cv_lars_1se", "lasso_cv_lars_min", "lasso_glmnet_bin_AICc", "lasso_glmnet_bin_BIC", "lasso_msgps_AICc", "lasso_msgps_BIC", "lasso_msgps_Cp", "lasso_msgps_GCV", "var_select" ] }, { "page": "var_select_all", "title": "Variable selection functions (all)", "concept": [ "Variable selection functions" ], "topics": [ "alasso_enet_msgps_all", "alasso_msgps_all", "enet_msgps_all", "lasso_cv_glmnet_all_5f", "lasso_cv_glmnet_bin_all", "lasso_glmnet_bin_all", "lasso_msgps_all", "sgpls_spls_all", "splsda_spls_all", "spls_spls_all", "varbvs_binomial_all", "varbvs_linear_all", "var_select_all" ] } ], "_pkglogo": "https://github.com/fbertran/selectboost/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/fbertran/selectboost/raw/HEAD/README.md", "_rundeps": [ "abind", "animation", "Cascade", "cli", "cluster", "codetools", "cpp11", "curl", "deldir", "foreach", "glmnet", "glue", "igraph", "interp", "iterators", "jpeg", "lars", "lattice", "latticeExtra", "lifecycle", "limma", "magick", "magrittr", "MASS", "Matrix", "msgps", "nnet", "nnls", "nor1mix", "pkgconfig", "pls", "png", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "RcppParallel", "Rfast", "rlang", "shape", "spls", "statmod", "survival", "tnet", "varbvs", "vctrs", "VGAM", "zigg" ], "_score": 5.054613054556888, "_indexed": true, "_nocasepkg": "selectboost", "_universes": [ "fbertran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.3.0", "date": "2026-05-23T09:19:11.000Z", "distro": "noble", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "6acbb2513a91d64e29609ddbd95c11343812b38ca9477aedaf75b59b8f65e4e3", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.6.0", "os": "linux", "version": "2.3.0", "date": "2026-05-23T09:19:13.000Z", "distro": "noble", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "0a7f75667df9e1ffa97e8e7f8cafbcfeadefaa295f548bcdd1771b65f046b703", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.5.3", "os": "mac", "version": "2.3.0", "date": "2026-05-23T09:18:26.000Z", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "14c356f6f17d0f7a98ecceb22134923c6f47068dce836bc1f72382875a848c8c", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.6.0", "os": "mac", "version": "2.3.0", "date": "2026-05-23T09:18:27.000Z", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "cba55609b7e256b1873e68a4d7fff6f2260febf7cd7c0697951e7e2d6854e4be", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.6.0", "os": "wasm", "version": "2.3.0", "date": "2026-05-23T09:19:07.000Z", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "dc2dde7c7944bf9b0756a8587429e5002d5cc1097f757ba229fca0128225adea", "status": "success", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.7.0", "os": "win", "version": "2.3.0", "date": "2026-05-23T09:18:05.000Z", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "6dea98d9091cf8fcbdd3c9d80bd5a38a1480e4d2312ccb3e317d45061ba23194", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.5.3", "os": "win", "version": "2.3.0", "date": "2026-05-23T09:17:21.000Z", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "5f2242919e1fb10b112d2e7e3e8e092dcf01c56f3c21b04ca1f1f18574699ae9", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" }, { "r": "4.6.0", "os": "win", "version": "2.3.0", "date": "2026-05-23T09:17:37.000Z", "commit": "f6285dc106eb66f09a121ae645bb3f44bd4dc4c8", "fileid": "94ccb62b2e56ad732a4deeed3c306dd7fc3691d2668f564f6a2577fcbe27cb74", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fbertran/actions/runs/26328936137" } ] }