{ "_id": "6adf03a1bf30f5f47f1a6ab1", "Package": "dfr", "Title": "Dual Feature Reduction for SGL", "Version": "0.1.6", "Date": "2025-09-30", "Authors@R": "person(\"Fabio\", \"Feser\", role = c(\"aut\", \"cre\"), email = \"ff120@ic.ac.uk\",comment = c(ORCID = \"0009-0007-3088-9727\"))", "Maintainer": "Fabio Feser ", "Description": "Implementation of the Dual Feature Reduction (DFR)\napproach for the Sparse Group Lasso (SGL) and the Adaptive\nSparse Group Lasso (aSGL) (Feser and Evangelou (2024)\n). The DFR approach is a feature\nreduction approach that applies strong screening to reduce the\nfeature space before optimisation, leading to speed-up\nimprovements for fitting SGL (Simon et al. (2013)\n) and aSGL (Mendez-Civieta et\nal. (2020) and Poignard (2020)\n) models. DFR is implemented\nusing the Adaptive Three Operator Splitting (ATOS) (Pedregosa\nand Gidel (2018) ) algorithm,\nwith linear and logistic SGL models supported, both of which\ncan be fit using k-fold cross-validation. Dense and sparse\ninput matrices are supported.", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.1", "License": "GPL (>= 3)", "Encoding": "UTF-8", "URL": "https://github.com/ff1201/dfr", "BugReports": "https://github.com/ff1201/dfr/issues", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://ff1201.r-universe.dev", "Date/Publication": "2026-06-28 11:10:14 UTC", "RemoteUrl": "https://github.com/ff1201/dfr", "RemoteRef": "HEAD", "RemoteSha": "e3088c9c8eba4e979834d1c3bd70dfb524ff264f", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-26 07:05:20 UTC", "User": "root" }, "Author": "Fabio Feser [aut, cre] (ORCID: )", "_user": "ff1201", "_type": "src", "_file": "dfr_0.1.6.tar.gz", "_fileid": "https://r2.ropensci.org/85ced8ea47dcf67f7d41cb2dbf1f6470dd52c7a1d92947a9dce0955864c377b6", "_filesize": 317849, "_sha256": "85ced8ea47dcf67f7d41cb2dbf1f6470dd52c7a1d92947a9dce0955864c377b6", "_expires": "2027-02-03T07:39:11.000Z", "_created": "2026-10-26T07:05:20.000Z", "_published": "2026-10-26T07:39:13.016Z", "_upstream": "https://github.com/ff1201/dfr", "_status": "success", "_maintainer": { "name": "Fabio Feser", "email": "ff120@ic.ac.uk", "orcid": "0009-0007-3088-9727" }, "_jobs": [ { "job": 121442350885, "time": 212, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "12633441154" }, { "job": 121442351068, "time": 410, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "12633342593" }, { "job": 121442351041, "time": 139, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "12634766033" }, { "job": 121442351000, "time": 167, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "12634920187" }, { "job": 121440136443, "time": 430, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "12633286805" }, { "job": 121442350970, "time": 308, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "12633481246" }, { "job": 121442351198, "time": 184, 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"package": "grDevices", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "Matrix", "role": "Imports" }, { "package": "SGL", "role": "Suggests" }, { "package": "gglasso", "role": "Suggests" }, { "package": "glmnet", "role": "Suggests" }, { "package": "testthat", "role": "Suggests" } ], "_owner": "ff1201", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-26", "n": 1 } ], "_tags": [], "_stars": 1, "_contributors": [ { "user": "ff1201", "count": 9, "uuid": 79450502 } ], "_userbio": { "uuid": 79450502, "type": "user", "name": "Fabio Feser", "followers": 4, "description": "PhD student on the StatML programme at Imperial & Oxford" }, "_downloads": { "count": 289, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/dfr" }, "_devurl": "https://github.com/ff1201/dfr", "_searchresults": 2, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/dfr.html", "extra/manual.pdf", "extra/readme.html", "extra/readme.md" ], "_homeurl": "https://github.com/ff1201/dfr", "_realowner": "ff1201", "_cranurl": true, "_releases": [ { "version": "0.1.0", "date": "2024-09-26" }, { "version": "0.1.1", "date": "2024-11-16" }, { "version": "0.1.2", "date": "2024-11-28" }, { "version": "0.1.3", "date": "2025-02-03" }, { "version": "0.1.4", "date": "2025-02-06" }, { "version": "0.1.5", "date": "2025-03-06" }, { "version": "0.1.6", "date": "2025-10-03" } ], "_exports": [ "dfr_adap_sgl", "dfr_adap_sgl.cv", "dfr_sgl", "dfr_sgl.cv" ], "_help": [ { "page": "dfr_adap_sgl", "title": "Fit a DFR-aSGL model.", "concept": [ "SGL-methods" ], "topics": [ "dfr_adap_sgl" ] }, { "page": "dfr_adap_sgl.cv", "title": "Fit a DFR-aSGL model using k-fold cross-validation.", "concept": [ "SGL-methods" ], "topics": [ "dfr_adap_sgl.cv" ] }, { "page": "dfr_sgl", "title": "Fit a DFR-SGL model.", "concept": [ "SGL-methods" ], "topics": [ "dfr_sgl" ] }, { "page": "dfr_sgl.cv", "title": "Fit a DFR-SGL model using k-fold cross-validation.", "concept": [ "SGL-methods" ], "topics": [ "dfr_sgl.cv" ] }, { "page": "plot.sgl", "title": "Plot models of the following object types: '\"sgl\"', '\"sgl_cv\"'.", "concept": [ "SGL-methods" ], "topics": [ "plot.sgl" ] }, { "page": "predict.sgl", "title": "Predict using one of the following object types: '\"sgl\"', '\"sgl_cv\"'.", "concept": [ "SGL-methods" ], "topics": [ "predict.sgl" ] }, { "page": "print.sgl", "title": "Prints information for one of the following object types: '\"sgl\"', '\"sgl_cv\"'.", "concept": [ "SGL-methods" ], "topics": [ "print.sgl" ] } ], "_readme": "https://github.com/ff1201/dfr/raw/HEAD/README.md", "_rundeps": [ "BH", "bigmemory", "bigmemory.sri", "caret", "class", "cli", "clock", "codetools", "cpp11", "data.table", "diagram", "digest", "dplyr", "e1071", "farver", "foreach", "future", "future.apply", "generics", "ggplot2", "globals", "glue", "gower", "gtable", "hardhat", "ipred", 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