{
  "_id": "6a1d3bfa1d7bb097a0a3f3d9",
  "Package": "rags2ridges",
  "Type": "Package",
  "Title": "Ridge Estimation of Precision Matrices from High-Dimensional\nData",
  "Version": "2.2.9",
  "Maintainer": "Carel F.W. Peeters <carel.peeters@wur.nl>",
  "Authors@R": "c(\nperson(given = c(\"Carel\", \"F.W.\"),\nfamily = \"Peeters\",\nemail = \"carel.peeters@wur.nl\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-5766-9969\")),\nperson(given = c(\"Anders\", \"Ellern\"),\nfamily = \"Bilgrau\",\nrole = c(\"aut\", \"cph\"),\nemail = \"anders.ellern.bilgrau@gmail.com\",\ncomment = c(ORCID = \"0000-0001-9875-2902\")),\nperson(given = c(\"Wessel\", \"N.\"),\nfamily = \"van Wieringen\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-5100-9123\"))\n)",
  "Description": "Proper L2-penalized maximum likelihood estimators for\nprecision matrices and supporting functions to employ these\nestimators in a graphical modeling setting. For details, see\nPeeters, Bilgrau, & van Wieringen (2022)\n<doi:10.18637/jss.v102.i04> and associated publications.",
  "biocViews": "",
  "KeepSource": "yes",
  "License": "GPL (>= 2)",
  "URL": "https://cfwp.github.io/rags2ridges/,\nhttps://github.com/CFWP/rags2ridges",
  "RoxygenNote": "7.2.3",
  "Encoding": "UTF-8",
  "VignetteBuilder": "knitr",
  "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libuv1-dev\nlibxml2-dev",
  "Repository": "https://cfwp.r-universe.dev",
  "Date/Publication": "2025-12-01 09:40:25 UTC",
  "RemoteUrl": "https://github.com/cfwp/rags2ridges",
  "RemoteRef": "HEAD",
  "RemoteSha": "929a3b4962c60444d6bbe782c62d466d07429f13",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-01 07:51:18 UTC",
    "User": "root"
  },
  "Author": "Carel F.W. Peeters [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0001-5766-9969>),\nAnders Ellern Bilgrau [aut, cph] (ORCID:\n<https://orcid.org/0000-0001-9875-2902>),\nWessel N. van Wieringen [aut] (ORCID:\n<https://orcid.org/0000-0002-5100-9123>)",
  "MD5sum": "abc84822cb0438bc7806ea1b78529901",
  "_user": "cfwp",
  "_type": "src",
  "_file": "rags2ridges_2.2.9.tar.gz",
  "_fileid": "49444c32d18c87acd1842338a0d6995b271fc8ad570a37db91ae32f091bf1d74",
  "_filesize": 954680,
  "_sha256": "49444c32d18c87acd1842338a0d6995b271fc8ad570a37db91ae32f091bf1d74",
  "_created": "2026-06-01T07:51:18.000Z",
  "_published": "2026-06-01T07:59:54.417Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 78808873902,
      "time": 248,
      "config": "linux-devel-arm64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7326152346"
    },
    {
      "job": 78808873919,
      "time": 208,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7326140362"
    },
    {
      "job": 78808873911,
      "time": 233,
      "config": "linux-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326148306"
    },
    {
      "job": 78808873925,
      "time": 255,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326154838"
    },
    {
      "job": 78808873942,
      "time": 191,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7326139904"
    },
    {
      "job": 78808873916,
      "time": 428,
      "config": "macos-oldrel-x86_64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7326213348"
    },
    {
      "job": 78808873928,
      "time": 272,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326172335"
    },
    {
      "job": 78808873929,
      "time": 292,
      "config": "macos-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326176148"
    },
    {
      "job": 78808296494,
      "time": 242,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326076453"
    },
    {
      "job": 78808873863,
      "time": 151,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326121909"
    },
    {
      "job": 78808873923,
      "time": 269,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7326159058"
    },
    {
      "job": 78808873913,
      "time": 243,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7326151025"
    },
    {
      "job": 78808873981,
      "time": 312,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7326172323"
    }
  ],
  "_buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cfwp/rags2ridges",
  "_commit": {
    "id": "929a3b4962c60444d6bbe782c62d466d07429f13",
    "author": "CFWP <carel.peeters@wur.nl>",
    "committer": "CFWP <carel.peeters@wur.nl>",
    "message": "testthat fixes\n",
    "time": 1764582025
  },
  "_maintainer": {
    "name": "Carel F.W. Peeters",
    "email": "carel.peeters@wur.nl",
    "login": "cfwp",
    "description": "Statistician specializing in multivariate and high-dimensional statistical learning",
    "uuid": 11041209,
    "orcid": "0000-0001-5766-9969"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 2.15.1",
      "role": "Depends"
    },
    {
      "package": "Rcpp",
      "role": "LinkingTo"
    },
    {
      "package": "RcppArmadillo",
      "role": "LinkingTo"
    },
    {
      "package": "igraph",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "expm",
      "role": "Imports"
    },
    {
      "package": "reshape",
      "role": "Imports"
    },
    {
      "package": "ggplot2",
      "role": "Imports"
    },
    {
      "package": "Hmisc",
      "role": "Imports"
    },
    {
      "package": "fdrtool",
      "role": "Imports"
    },
    {
      "package": "snowfall",
      "role": "Imports"
    },
    {
      "package": "sfsmisc",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "grDevices",
      "role": "Imports"
    },
    {
      "package": "graphics",
      "role": "Imports"
    },
    {
      "package": "gRbase",
      "role": "Imports"
    },
    {
      "package": "RBGL",
      "role": "Imports"
    },
    {
      "package": "graph",
      "role": "Imports"
    },
    {
      "package": "Rcpp",
      "role": "Imports"
    },
    {
      "package": "RSpectra",
      "role": "Imports"
    },
    {
      "package": "KEGGgraph",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "cfwp",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2025-35",
      "n": 7
    },
    {
      "week": "2025-49",
      "n": 2
    }
  ],
  "_tags": [
    {
      "name": "v2.2.8",
      "date": "2025-08-29"
    },
    {
      "name": "V2.2.9-beta",
      "date": "2025-12-01"
    }
  ],
  "_topics": [
    "c-plus-plus",
    "graphical-models",
    "machine-learning",
    "networkscience",
    "statistics",
    "openblas",
    "cpp"
  ],
  "_stars": 8,
  "_contributors": [
    {
      "user": "aebilgrau",
      "count": 385,
      "uuid": 6087024
    },
    {
      "user": "cfwp",
      "count": 377,
      "uuid": 11041209
    },
    {
      "user": "wvanwie",
      "count": 12,
      "uuid": 16555533
    }
  ],
  "_userbio": {
    "uuid": 11041209,
    "type": "user",
    "name": "Carel F.W. Peeters",
    "description": "Statistician specializing in multivariate and high-dimensional statistical learning"
  },
  "_downloads": {
    "count": 811,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/rags2ridges"
  },
  "_mentions": 1,
  "_devurl": "https://github.com/cfwp/rags2ridges",
  "_pkgdown": "https://cfwp.github.io/rags2ridges/",
  "_searchresults": 57,
  "_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/rags2ridges.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/cfwp/rags2ridges",
  "_realowner": "cfwp",
  "_cranurl": true,
  "_releases": [
    {
      "version": "1.1",
      "date": "2014-03-07"
    },
    {
      "version": "1.2",
      "date": "2014-05-06"
    },
    {
      "version": "1.3",
      "date": "2014-08-06"
    },
    {
      "version": "1.4",
      "date": "2014-11-28"
    },
    {
      "version": "2.0",
      "date": "2015-10-15"
    },
    {
      "version": "2.1",
      "date": "2016-08-12"
    },
    {
      "version": "2.1.1",
      "date": "2016-08-18"
    },
    {
      "version": "2.2",
      "date": "2017-04-13"
    },
    {
      "version": "2.2.1",
      "date": "2019-03-19"
    },
    {
      "version": "2.2.2",
      "date": "2019-12-17"
    },
    {
      "version": "2.2.3",
      "date": "2020-08-28"
    },
    {
      "version": "2.2.4",
      "date": "2020-12-08"
    },
    {
      "version": "2.2.5",
      "date": "2021-06-07"
    },
    {
      "version": "2.2.6",
      "date": "2022-05-01"
    },
    {
      "version": "2.2.7",
      "date": "2023-10-14"
    },
    {
      "version": "2.2.8",
      "date": "2025-08-29"
    },
    {
      "version": "2.2.9",
      "date": "2025-12-01"
    }
  ],
  "_exports": [
    "adjacentMat",
    "CNplot",
    "Communities",
    "conditionNumberPlot",
    "covML",
    "covMLknown",
    "createS",
    "default.penalty",
    "default.target",
    "default.target.fused",
    "DiffGraph",
    "edgeHeat",
    "evaluateS",
    "evaluateSfit",
    "fullMontyS",
    "fused.test",
    "getKEGGPathway",
    "GGMblockNullPenalty",
    "GGMblockTest",
    "GGMmutualInfo",
    "GGMnetworkStats",
    "GGMnetworkStats.fused",
    "GGMpathStats",
    "GGMpathStats.fused",
    "is.Xlist",
    "isSymmetricPD",
    "isSymmetricPSD",
    "kegg.target",
    "KLdiv",
    "KLdiv.fused",
    "loss",
    "momentS",
    "NLL",
    "NLL.fused",
    "optPenalty.aLOOCV",
    "optPenalty.fused",
    "optPenalty.fused.auto",
    "optPenalty.fused.grid",
    "optPenalty.kCV",
    "optPenalty.kCVauto",
    "optPenalty.LOOCV",
    "optPenalty.LOOCVauto",
    "pcor",
    "PNLL",
    "PNLL.fused",
    "pooledP",
    "pooledS",
    "pruneMatrix",
    "ridgeP",
    "ridgeP.fused",
    "ridgePathS",
    "ridgeS",
    "rmvnormal",
    "sparsify",
    "sparsify.fused",
    "symm",
    "Ugraph",
    "Union"
  ],
  "_datasets": [
    {
      "name": "ADmetabolites",
      "title": "R-objects related to metabolomics data on patients with Alzheimer's Disease",
      "object": "ADdata",
      "file": "ADdata.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "Sample_1",
        "Sample_2",
        "Sample_3",
        "Sample_4",
        "Sample_5",
        "Sample_6",
        "Sample_7",
        "Sample_8",
        "Sample_9",
        "Sample_10",
        "Sample_11",
        "Sample_12",
        "Sample_13",
        "Sample_14",
        "Sample_15",
        "Sample_16",
        "Sample_17",
        "Sample_18",
        "Sample_19",
        "Sample_20",
        "Sample_21",
        "Sample_22",
        "Sample_23",
        "Sample_24",
        "Sample_25",
        "Sample_26",
        "Sample_27",
        "Sample_28",
        "Sample_29",
        "Sample_30",
        "Sample_31",
        "Sample_32",
        "Sample_33",
        "Sample_34",
        "Sample_35",
        "Sample_36",
        "Sample_37",
        "Sample_38",
        "Sample_39",
        "Sample_40",
        "Sample_41",
        "Sample_42",
        "Sample_43",
        "Sample_44",
        "Sample_45",
        "Sample_46",
        "Sample_47",
        "Sample_48",
        "Sample_49",
        "Sample_50",
        "Sample_51",
        "Sample_52",
        "Sample_53",
        "Sample_54",
        "Sample_55",
        "Sample_56",
        "Sample_57",
        "Sample_58",
        "Sample_59",
        "Sample_60",
        "Sample_61",
        "Sample_62",
        "Sample_63",
        "Sample_64",
        "Sample_65",
        "Sample_66",
        "Sample_67",
        "Sample_68",
        "Sample_69",
        "Sample_70",
        "Sample_71",
        "Sample_72",
        "Sample_73",
        "Sample_74",
        "Sample_75",
        "Sample_76",
        "Sample_77",
        "Sample_78",
        "Sample_79",
        "Sample_80",
        "Sample_81",
        "Sample_82",
        "Sample_83",
        "Sample_84",
        "Sample_85",
        "Sample_86",
        "Sample_87",
        "Sample_88",
        "Sample_89",
        "Sample_90",
        "Sample_91",
        "Sample_92",
        "Sample_93",
        "Sample_94",
        "Sample_95",
        "Sample_96",
        "Sample_97",
        "Sample_98",
        "Sample_99",
        "Sample_100",
        "Sample_101",
        "Sample_102",
        "Sample_103",
        "Sample_104",
        "Sample_105",
        "Sample_106",
        "Sample_107",
        "Sample_108",
        "Sample_109",
        "Sample_110",
        "Sample_111",
        "Sample_112",
        "Sample_113",
        "Sample_114",
        "Sample_115",
        "Sample_116",
        "Sample_117",
        "Sample_118",
        "Sample_119",
        "Sample_120",
        "Sample_121",
        "Sample_122",
        "Sample_123",
        "Sample_124",
        "Sample_125",
        "Sample_126",
        "Sample_127"
      ],
      "rows": 230,
      "table": true,
      "tojson": true
    },
    {
      "name": "sampleInfo",
      "title": "R-objects related to metabolomics data on patients with Alzheimer's Disease",
      "object": "ADdata",
      "file": "ADdata.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Diagnosis",
        "ApoEClass"
      ],
      "rows": 127,
      "table": true,
      "tojson": true
    },
    {
      "name": "variableInfo",
      "title": "R-objects related to metabolomics data on patients with Alzheimer's Disease",
      "object": "ADdata",
      "file": "ADdata.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Family",
        "FamilyCode"
      ],
      "rows": 230,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "rags2ridges-package",
      "title": "Ridge estimation for high-dimensional precision matrices",
      "topics": [
        "rags2ridges-package",
        "rags2ridges"
      ]
    },
    {
      "page": "ADdata",
      "title": "R-objects related to metabolomics data on patients with Alzheimer's Disease",
      "topics": [
        "ADdata",
        "ADmetabolites",
        "sampleInfo",
        "variableInfo"
      ]
    },
    {
      "page": "adjacentMat",
      "title": "Transform real matrix into an adjacency matrix",
      "topics": [
        "adjacentMat"
      ]
    },
    {
      "page": "CNplot",
      "title": "Visualize the spectral condition number against the regularization parameter",
      "topics": [
        "CNplot"
      ]
    },
    {
      "page": "Communities",
      "title": "Search and visualize community-structures",
      "topics": [
        "Communities"
      ]
    },
    {
      "page": "conditionNumberPlot",
      "title": "Visualize the spectral condition number against the regularization parameter",
      "topics": [
        "conditionNumberPlot"
      ]
    },
    {
      "page": "covML",
      "title": "Maximum likelihood estimation of the covariance matrix",
      "topics": [
        "covML"
      ]
    },
    {
      "page": "covMLknown",
      "title": "Maximum likelihood estimation of the covariance matrix with assumptions on its structure",
      "topics": [
        "covMLknown"
      ]
    },
    {
      "page": "createS",
      "title": "Simulate sample covariances or datasets",
      "topics": [
        "createS"
      ]
    },
    {
      "page": "default.penalty",
      "title": "Construct commonly used penalty matrices",
      "topics": [
        "default.penalty"
      ]
    },
    {
      "page": "default.target",
      "title": "Generate a (data-driven) default target for usage in ridge-type shrinkage estimation",
      "topics": [
        "default.target"
      ]
    },
    {
      "page": "default.target.fused",
      "title": "Generate data-driven targets for fused ridge estimation",
      "topics": [
        "default.target.fused"
      ]
    },
    {
      "page": "DiffGraph",
      "title": "Visualize the differential graph",
      "topics": [
        "DiffGraph"
      ]
    },
    {
      "page": "edgeHeat",
      "title": "Visualize (precision) matrix as a heatmap",
      "topics": [
        "edgeHeat"
      ]
    },
    {
      "page": "evaluateS",
      "title": "Evaluate numerical properties square matrix",
      "topics": [
        "evaluateS"
      ]
    },
    {
      "page": "evaluateSfit",
      "title": "Visual inspection of the fit of a regularized precision matrix",
      "topics": [
        "evaluateSfit"
      ]
    },
    {
      "page": "fullMontyS",
      "title": "Wrapper function",
      "topics": [
        "fullMontyS"
      ]
    },
    {
      "page": "fused.test",
      "title": "Test the necessity of fusion",
      "topics": [
        "fused.test"
      ]
    },
    {
      "page": "GGMblockNullPenalty",
      "title": "Generate the distribution of the penalty parameter under the null hypothesis of block-independence",
      "topics": [
        "GGMblockNullPenalty"
      ]
    },
    {
      "page": "GGMblockTest",
      "title": "Test for block-indepedence",
      "topics": [
        "GGMblockTest"
      ]
    },
    {
      "page": "GGMmutualInfo",
      "title": "Mutual information between two sets of variates within a multivariate normal distribution",
      "topics": [
        "GGMmutualInfo"
      ]
    },
    {
      "page": "GGMnetworkStats",
      "title": "Gaussian graphical model network statistics",
      "topics": [
        "GGMnetworkStats"
      ]
    },
    {
      "page": "GGMnetworkStats.fused",
      "title": "Gaussian graphical model network statistics",
      "topics": [
        "GGMnetworkStats.fused"
      ]
    },
    {
      "page": "GGMpathStats",
      "title": "Gaussian graphical model node pair path statistics",
      "topics": [
        "GGMpathStats"
      ]
    },
    {
      "page": "GGMpathStats.fused",
      "title": "Fused gaussian graphical model node pair path statistics",
      "topics": [
        "GGMpathStats.fused"
      ]
    },
    {
      "page": "plot.ptest",
      "title": "Plot the results of a fusion test",
      "topics": [
        "hist.ptest",
        "plot.ptest"
      ]
    },
    {
      "page": "is.Xlist",
      "title": "Test if fused list-formats are correctly used",
      "topics": [
        "is.Xlist"
      ]
    },
    {
      "page": "isSymmetricPD",
      "title": "Test for symmetric positive (semi-)definiteness",
      "topics": [
        "isSymmetricPD",
        "isSymmetricPSD"
      ]
    },
    {
      "page": "kegg.target",
      "title": "Construct target matrix from KEGG",
      "topics": [
        "kegg.target"
      ]
    },
    {
      "page": "KLdiv",
      "title": "Kullback-Leibler divergence between two multivariate normal distributions",
      "topics": [
        "KLdiv"
      ]
    },
    {
      "page": "KLdiv.fused",
      "title": "Fused Kullback-Leibler divergence for sets of distributions",
      "topics": [
        "KLdiv.fused"
      ]
    },
    {
      "page": "loss",
      "title": "Evaluate regularized precision under various loss functions",
      "topics": [
        "loss"
      ]
    },
    {
      "page": "momentS",
      "title": "Moments of the sample covariance matrix.",
      "topics": [
        "momentS"
      ]
    },
    {
      "page": "NLL",
      "title": "Evaluate the (penalized) (fused) likelihood",
      "topics": [
        "NLL",
        "NLL.fused",
        "PNLL",
        "PNLL.fused"
      ]
    },
    {
      "page": "optPenalty.aLOOCV",
      "title": "Select optimal penalty parameter by approximate leave-one-out cross-validation",
      "topics": [
        "optPenalty.aLOOCV"
      ]
    },
    {
      "page": "optPenalty.fused",
      "title": "Identify optimal ridge and fused ridge penalties",
      "topics": [
        "optPenalty.fused",
        "optPenalty.fused.auto",
        "optPenalty.fused.grid"
      ]
    },
    {
      "page": "optPenalty.kCV",
      "title": "Select optimal penalty parameter by K-fold cross-validation",
      "topics": [
        "optPenalty.kCV"
      ]
    },
    {
      "page": "optPenalty.kCVauto",
      "title": "Automatic search for optimal penalty parameter",
      "topics": [
        "optPenalty.kCVauto"
      ]
    },
    {
      "page": "optPenalty.LOOCV",
      "title": "Select optimal penalty parameter by leave-one-out cross-validation",
      "topics": [
        "optPenalty.LOOCV"
      ]
    },
    {
      "page": "optPenalty.LOOCVauto",
      "title": "Automatic search for optimal penalty parameter",
      "topics": [
        "optPenalty.LOOCVauto"
      ]
    },
    {
      "page": "pcor",
      "title": "Compute partial correlation matrix or standardized precision matrix",
      "topics": [
        "pcor"
      ]
    },
    {
      "page": "pooledS",
      "title": "Compute the pooled covariance or precision matrix estimate",
      "topics": [
        "pooledP",
        "pooledS"
      ]
    },
    {
      "page": "print.optPenaltyFusedGrid",
      "title": "Print and plot functions for fused grid-based cross-validation",
      "topics": [
        "plot.optPenaltyFusedGrid",
        "print.optPenaltyFusedGrid"
      ]
    },
    {
      "page": "print.ptest",
      "title": "Print and summarize fusion test",
      "topics": [
        "print.ptest",
        "summary.ptest"
      ]
    },
    {
      "page": "pruneMatrix",
      "title": "Prune square matrix to those variables having nonzero entries",
      "topics": [
        "pruneMatrix"
      ]
    },
    {
      "page": "ridgeP",
      "title": "Ridge estimation for high-dimensional precision matrices",
      "topics": [
        "ridgeP"
      ]
    },
    {
      "page": "ridgeP.fused",
      "title": "Fused ridge estimation",
      "topics": [
        "ridgeP.fused"
      ]
    },
    {
      "page": "ridgePathS",
      "title": "Visualize the regularization path",
      "topics": [
        "ridgePathS"
      ]
    },
    {
      "page": "ridgeS",
      "title": "Ridge estimation for high-dimensional precision matrices",
      "topics": [
        "ridgeS"
      ]
    },
    {
      "page": "rmvnormal",
      "title": "Multivariate Gaussian simulation",
      "topics": [
        "rmvnormal"
      ]
    },
    {
      "page": "sparsify",
      "title": "Determine the support of a partial correlation/precision matrix",
      "topics": [
        "sparsify"
      ]
    },
    {
      "page": "sparsify.fused",
      "title": "Determine support of multiple partial correlation/precision matrices",
      "topics": [
        "sparsify.fused"
      ]
    },
    {
      "page": "symm",
      "title": "Symmetrize matrix",
      "topics": [
        "symm"
      ]
    },
    {
      "page": "Ugraph",
      "title": "Visualize undirected graph",
      "topics": [
        "Ugraph"
      ]
    },
    {
      "page": "Union",
      "title": "Subset 2 square matrices to union of variables having nonzero entries",
      "topics": [
        "Union"
      ]
    }
  ],
  "_readme": "https://github.com/cfwp/rags2ridges/raw/HEAD/README.md",
  "_rundeps": [
    "backports",
    "base64enc",
    "BH",
    "BiocGenerics",
    "bslib",
    "cachem",
    "checkmate",
    "cli",
    "cluster",
    "colorspace",
    "cpp11",
    "data.table",
    "digest",
    "evaluate",
    "expm",
    "farver",
    "fastmap",
    "fdrtool",
    "fontawesome",
    "foreign",
    "Formula",
    "fs",
    "generics",
    "ggplot2",
    "glue",
    "graph",
    "gRbase",
    "gridExtra",
    "gtable",
    "highr",
    "Hmisc",
    "htmlTable",
    "htmltools",
    "htmlwidgets",
    "igraph",
    "isoband",
    "jquerylib",
    "jsonlite",
    "knitr",
    "labeling",
    "lattice",
    "lifecycle",
    "magrittr",
    "Matrix",
    "memoise",
    "mime",
    "nnet",
    "pkgconfig",
    "plyr",
    "R6",
    "rappdirs",
    "RBGL",
    "RColorBrewer",
    "Rcpp",
    "RcppArmadillo",
    "RcppEigen",
    "reshape",
    "rlang",
    "rmarkdown",
    "rpart",
    "RSpectra",
    "rstudioapi",
    "S7",
    "sass",
    "scales",
    "sfsmisc",
    "snow",
    "snowfall",
    "stringi",
    "stringr",
    "tinytex",
    "vctrs",
    "viridisLite",
    "withr",
    "xfun",
    "yaml"
  ],
  "_sysdeps": [
    {
      "shlib": "liblapack",
      "package": "libopenblas0-pthread",
      "source": "openblas",
      "version": "0.3.26+ds-1ubuntu0.1",
      "name": "openblas",
      "homepage": "https://www.openblas.net/",
      "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)"
    },
    {
      "shlib": "libblas",
      "package": "libopenblas0-pthread",
      "source": "openblas",
      "version": "0.3.26+ds-1ubuntu0.1",
      "name": "openblas",
      "homepage": "https://www.openblas.net/",
      "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)"
    },
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
  ],
  "_vignettes": [
    {
      "source": "rags2ridges.Rmd",
      "filename": "rags2ridges.html",
      "title": "Introduction to rags2ridges",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Getting started",
        "Package installation",
        "Small theoretical primer and package usage",
        "The penalty parameter",
        "The target matrix",
        "Gaussian graphical modeling and post processing",
        "What is so interesting with the precision matrix anyway? I'm always interested in correlations and thus the correlation matrix.",
        "OK, but what is graphical about the graphical ridge estimate?",
        "Graphical ridge estimation? Why not graphical Lasso?",
        "How do I select the edges then?",
        "Concluding remarks",
        "References"
      ],
      "created": "2020-01-19 13:57:35",
      "modified": "2025-08-29 15:17:00",
      "commits": 16
    }
  ],
  "_score": 5.9599948383284165,
  "_indexed": true,
  "_nocasepkg": "rags2ridges",
  "_universes": [
    "cfwp"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:25.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "c7eaa6ee8dd2389767ba8ba965fafb356384227055bfab38d1e196e780446684",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:07.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "876043a92284d6454fc48707b265689e13eaf68f5d7d182cb0f7991bff474e41",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:17.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "a1197eefd987ae5b84828669565f5f834e57c00554480119221d26b32a69464e",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:27.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "85d901c58679e99134ae720a7c5d62097186330360ca235d7d8a449f77114d9d",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:06.000Z",
      "arch": "aarch64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "0efc398a804e27cd8a975080b216d488cd820ebf36289bc53ad9cdf9d05a3156",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "2.2.9",
      "date": "2026-06-01T07:56:08.000Z",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "894c465bccc473461ea34e066f86a2e3f8b836b18c33ada3f4407b972b317e85",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:54.000Z",
      "arch": "aarch64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "6a1ac622217166a949b3689294585675afcc4e30f2d15d49d8fdd7f89142e701",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "2.2.9",
      "date": "2026-06-01T07:55:04.000Z",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "51a0949596418762e8ee1253ec2ed36e4b0bdcddf4ca4ead78c654715d81bfc5",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "2.2.9",
      "date": "2026-06-01T07:54:25.000Z",
      "arch": "emscripten",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "54954ac3de6298441a0fd695082c4848692694e0de0ae54014486653c0ab0e5b",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "2.2.9",
      "date": "2026-06-01T07:53:48.000Z",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "c77141813afb6832414567beb0ef23f3f369ca9ace67440ed93c58007d45f39a",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "2.2.9",
      "date": "2026-06-01T07:53:26.000Z",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "8fb23b007de75cc8f6947e7a304b3c6e1ad0825c33475878b3a7e8f40199f91a",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "2.2.9",
      "date": "2026-06-01T07:53:37.000Z",
      "arch": "x86_64",
      "commit": "929a3b4962c60444d6bbe782c62d466d07429f13",
      "fileid": "bf8eeef51cfcaa7ec1366d0f3c3526a8b1c7d10f5ca5ea042faf4f1f7483f931",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cfwp/actions/runs/26742065219"
    }
  ]
}