{ "_id": "6a16a1eaacfb0bcc41d815f3", "Package": "SLOPE", "Title": "Sorted L1 Penalized Estimation", "Version": "2.1.0", "Authors@R": "c(\nperson(\n\"Johan\",\n\"Larsson\",\nrole = c(\"aut\", \"cre\"),\nemail = \"johan@jolars.co\",\ncomment = c(ORCID = \"0000-0002-4029-5945\")\n),\nperson(\n\"Jonas\",\n\"Wallin\",\nrole = \"aut\",\nemail = \"jonas.wallin@stat.lu.se\",\ncomment = c(ORCID = \"0000-0003-0381-6593\")\n),\nperson(\n\"Malgorzata\",\n\"Bogdan\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-0657-4342\")\n),\nperson(\"Ewout\", \"van den Berg\", role = \"aut\"),\nperson(\"Chiara\", \"Sabatti\", role = \"aut\"),\nperson(\"Emmanuel\", \"Candes\", role = \"aut\"),\nperson(\"Evan\", \"Patterson\", role = \"aut\"),\nperson(\"Weijie\", \"Su\", role = \"aut\"),\nperson(\"Jakub\", \"Kała\", role = \"aut\"),\nperson(\"Krystyna\", \"Grzesiak\", role = \"aut\"),\nperson(\"Mathurin\", \"Massias\", role = \"aut\"),\nperson(\"Quentin\", \"Klopfenstein\", role = \"aut\"),\nperson(\n\"Michal\",\n\"Burdukiewicz\",\ncomment = c(ORCID = \"0000-0001-8926-582X\"),\nrole = \"aut\"\n),\nperson(\n\"Jerome\",\n\"Friedman\",\nrole = \"ctb\",\ncomment = \"code adapted from 'glmnet'\"\n),\nperson(\n\"Trevor\",\n\"Hastie\",\nrole = \"ctb\",\ncomment = \"code adapted from 'glmnet'\"\n),\nperson(\n\"Rob\",\n\"Tibshirani\",\nrole = \"ctb\",\ncomment = \"code adapted from 'glmnet'\"\n),\nperson(\n\"Balasubramanian\",\n\"Narasimhan\",\nrole = \"ctb\",\ncomment = \"code adapted from 'glmnet'\"\n),\nperson(\n\"Noah\",\n\"Simon\",\nrole = \"ctb\",\ncomment = \"code adapted from 'glmnet'\"\n),\nperson(\n\"Junyang\",\n\"Qian\",\nrole = \"ctb\",\ncomment = \"code adapted from 'glmnet'\"\n)\n)", "Description": "Efficient implementations for Sorted L-One Penalized\nEstimation (SLOPE): generalized linear models regularized with\nthe sorted L1-norm (Bogdan et al. 2015). Supported models\ninclude ordinary least-squares regression, binomial regression,\nmultinomial regression, and Poisson regression. Both dense and\nsparse predictor matrices are supported. 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Tibshirani [ctb] (code adapted from\n'glmnet'), Balasubramanian Narasimhan [ctb] (code adapted from\n'glmnet'), Noah Simon [ctb] (code adapted from 'glmnet'),\nJunyang Qian [ctb] (code adapted from 'glmnet')", "Maintainer": "Johan Larsson ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-03-28 07:57:35 UTC", "RemoteUrl": "https://github.com/cran/SLOPE", "RemoteRef": "HEAD", "RemoteSha": "4ab6cf6d02e5755093ef8c8642a07e8dbcc7fc29", "MD5sum": "f4f05fc73c8fce23266771a6bcd6eb3e", "_user": "cran", "_type": "src", "_file": "SLOPE_2.1.0.tar.gz", "_fileid": "9fd8b6aee6bcde4aab13762dbec77efa9bffd44ba443ee3b1c0469638252b212", "_filesize": 1175553, "_sha256": "9fd8b6aee6bcde4aab13762dbec77efa9bffd44ba443ee3b1c0469638252b212", "_created": "2026-05-27T07:42:40.000Z", "_published": "2026-05-27T07:48:58.064Z", "_distro": "noble", "_jobs": [ { "job": 78030801058, "time": 256, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7234786901" }, { "job": 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