{
  "_id": "6a1031ebacfb0bcc41c9749d",
  "Package": "rCausalMGM",
  "Type": "Package",
  "Title": "Scalable Causal Discovery and Model Selection on Mixed Datasets\nwith 'rCausalMGM'",
  "Version": "1.0.1",
  "Date": "2026-03-13",
  "Author": "Tyler C Lovelace [aut], Max Dudek [aut], Jack Fiore [aut],\nPanayiotis V Benos [aut, cre]",
  "Authors@R": "c(person(given = c(\"Tyler\", \"C\"),\nfamily = \"Lovelace\",\nrole = \"aut\"),\nperson(given = \"Max\",\nfamily = \"Dudek\",\nrole = \"aut\"),\nperson(given = \"Jack\",\nfamily = \"Fiore\",\nrole = \"aut\"),\nperson(given = c(\"Panayiotis\", \"V\"),\nfamily = \"Benos\",\nrole = c(\"aut\", \"cre\"),\nemail = \"pbenos@ufl.edu\"))",
  "Maintainer": "Panayiotis V Benos <pbenos@ufl.edu>",
  "Description": "Scalable methods for learning causal graphical models from\nmixed data, including continuous, discrete, and censored\nvariables. The package implements CausalMGM, which combines a\nconvex, score-based approach for learning an initial moralized\ngraph with a producer-consumer scheme that enables efficient\nparallel conditional independence testing in constraint-based\ncausal discovery algorithms. The implementation supports\nhigh-dimensional datasets and provides individual access to\ncore components of the workflow, including MGM and the\nPC-Stable and FCI-Stable causal discovery algorithms. To\nsupport practical applications, the package includes multiple\nmodel selection strategies, including information criteria\nbased on likelihood and model complexity, cross-validation for\nout-of-sample likelihood estimation, and stability-based\napproaches that assess graph robustness across subsamples.",
  "License": "GPL-3",
  "RoxygenNote": "7.3.2",
  "Encoding": "UTF-8",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-05-12 09:14:07 UTC",
    "User": "root"
  },
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-03-13 19:00:02 UTC",
  "RemoteUrl": "https://github.com/cran/rCausalMGM",
  "RemoteRef": "HEAD",
  "RemoteSha": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
  "MD5sum": "cb9a5ce75259f4b16ff0dc2211d06bd0",
  "_user": "cran",
  "_type": "src",
  "_file": "rCausalMGM_1.0.1.tar.gz",
  "_fileid": "18c74e9b7544d2490331e34debbe9926d5a0f35739b58eab5caccced586cb726",
  "_filesize": 474129,
  "_sha256": "18c74e9b7544d2490331e34debbe9926d5a0f35739b58eab5caccced586cb726",
  "_created": "2026-05-12T09:14:07.000Z",
  "_published": "2026-05-22T10:37:31.907Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 77362375147,
      "time": 485,
      "config": "linux-devel-arm64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "6940454381"
    },
    {
      "job": 77362374923,
      "time": 478,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "6940451869"
    },
    {
      "job": 77362375231,
      "time": 523,
      "config": "linux-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6940467375"
    },
    {
      "job": 77362375281,
      "time": 445,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6940440652"
    },
    {
      "job": 77362374706,
      "time": 499,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6940282345"
    },
    {
      "job": 77362374623,
      "time": 390,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7158504751"
    }
  ],
  "_buildurl": "https://github.com/r-universe/cran/actions/runs/25724886459",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/rCausalMGM",
  "_commit": {
    "id": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
    "author": "Panayiotis V Benos <pbenos@ufl.edu>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 1.0.1\n",
    "time": 1773428402
  },
  "_maintainer": {
    "name": "Panayiotis V Benos",
    "email": "pbenos@ufl.edu"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "BH",
      "role": "LinkingTo"
    },
    {
      "package": "Rcpp",
      "role": "LinkingTo"
    },
    {
      "package": "RcppArmadillo",
      "role": "LinkingTo"
    },
    {
      "package": "RcppThread",
      "role": "LinkingTo"
    },
    {
      "package": "Rcpp",
      "version": ">= 1.0.3",
      "role": "Imports"
    },
    {
      "package": "survival",
      "role": "Imports"
    },
    {
      "package": "Rgraphviz",
      "role": "Suggests"
    },
    {
      "package": "graph",
      "role": "Suggests"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-10",
      "n": 1
    },
    {
      "week": "2026-11",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "1.0",
      "date": "2026-03-03"
    },
    {
      "name": "1.0.1",
      "date": "2026-03-13"
    }
  ],
  "_stars": 0,
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 511,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/rCausalMGM"
  },
  "_searchresults": 25,
  "_topics": [
    "openblas",
    "cpp",
    "openmp"
  ],
  "_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/rCausalMGM.html",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
    {
      "version": "1.0",
      "date": "2026-03-03"
    },
    {
      "version": "1.0.1",
      "date": "2026-03-13"
    }
  ],
  "_exports": [
    "adjMat2Graph",
    "allMetrics",
    "bootstrap",
    "boss",
    "coxmgm",
    "coxmgmCV",
    "coxmgmPath",
    "cpdag",
    "createKnowledge",
    "fciCV",
    "fciStable",
    "fciStars",
    "graphTable",
    "grasp",
    "growShrinkMB",
    "loadGraph",
    "mgm",
    "mgmCV",
    "mgmfciCV",
    "mgmPath",
    "mgmpcCV",
    "moral",
    "pag",
    "pcCV",
    "pcStable",
    "pcStars",
    "plot.graph",
    "plot.graphCV",
    "plot.graphPath",
    "plot.graphSTARS",
    "plot.graphSTEPS",
    "print.graph",
    "print.graphCV",
    "print.graphPath",
    "print.graphSTARS",
    "print.graphSTEPS",
    "print.knowledge",
    "printGraph",
    "prMetrics",
    "prMetricsAdjacency",
    "prMetricsCausal",
    "prMetricsOrientation",
    "saveGraph",
    "SHD",
    "simRandomDAG",
    "skeleton",
    "steps"
  ],
  "_help": [
    {
      "page": "adjMat2Graph",
      "title": "Convert an adjacency matrix into a graph",
      "topics": [
        "adjMat2Graph"
      ]
    },
    {
      "page": "allMetrics",
      "title": "Combined graph recovery metrics",
      "topics": [
        "allMetrics"
      ]
    },
    {
      "page": "bootstrap",
      "title": "Runs bootstrapping for a causal graph on the dataset.",
      "topics": [
        "bootstrap"
      ]
    },
    {
      "page": "boss",
      "title": "Runs the BOSS causal discovery algorithm on the dataset",
      "topics": [
        "boss"
      ]
    },
    {
      "page": "coxmgm",
      "title": "Calculate the CoxMGM graph on a dataset.",
      "topics": [
        "coxmgm"
      ]
    },
    {
      "page": "coxmgmCV",
      "title": "Implements k-fold cross-validation for CoxMGM",
      "topics": [
        "coxmgmCV"
      ]
    },
    {
      "page": "coxmgmPath",
      "title": "Estimates a solution path for CoxMGM",
      "topics": [
        "coxmgmPath"
      ]
    },
    {
      "page": "cpdag",
      "title": "Calculate the CPDAG for a given DAG",
      "topics": [
        "cpdag"
      ]
    },
    {
      "page": "createKnowledge",
      "title": "A function to create a prior knowledge object for use with causal discovery algorithms",
      "topics": [
        "createKnowledge"
      ]
    },
    {
      "page": "fciCV",
      "title": "Implements k-fold cross-validation for FCI-Stable",
      "topics": [
        "fciCV"
      ]
    },
    {
      "page": "fciStable",
      "title": "Runs the causal discovery algorithm FCI-Stable on a dataset.",
      "topics": [
        "fciStable"
      ]
    },
    {
      "page": "fciStars",
      "title": "Implements StARS for FCI-Stable",
      "topics": [
        "fciStars"
      ]
    },
    {
      "page": "graphTable",
      "title": "A function to generate a data.frame for objects from graph class. It incorporates adjacency and orientation frequency if estimates of edge stability are available.",
      "topics": [
        "graphTable"
      ]
    },
    {
      "page": "grasp",
      "title": "Runs the GRaSP causal discovery algorithm on the dataset",
      "topics": [
        "grasp"
      ]
    },
    {
      "page": "growShrinkMB",
      "title": "Implements Grow-Shrink algorithm for Markov blanket identification",
      "topics": [
        "growShrinkMB"
      ]
    },
    {
      "page": "loadGraph",
      "title": "Load a graph from a \".txt\" file",
      "topics": [
        "loadGraph"
      ]
    },
    {
      "page": "mgm",
      "title": "Calculate the Mixed Graphical Model (MGM) graph on a dataset.",
      "topics": [
        "mgm"
      ]
    },
    {
      "page": "mgmCV",
      "title": "Implements k-fold cross-validation for MGM",
      "topics": [
        "mgmCV"
      ]
    },
    {
      "page": "mgmfciCV",
      "title": "Implements k-fold cross-validation for MGM-FCI-Stable",
      "topics": [
        "mgmfciCV"
      ]
    },
    {
      "page": "mgmPath",
      "title": "Estimates a solution path for MGM",
      "topics": [
        "mgmPath"
      ]
    },
    {
      "page": "mgmpcCV",
      "title": "Implements k-fold cross-validation for MGM-PC-Stable",
      "topics": [
        "mgmpcCV"
      ]
    },
    {
      "page": "moral",
      "title": "Calculate the moral graph for a given DAG",
      "topics": [
        "moral"
      ]
    },
    {
      "page": "pag",
      "title": "Calculate the PAG for a given DAG and set of latent variables",
      "topics": [
        "pag"
      ]
    },
    {
      "page": "pcCV",
      "title": "Implements k-fold cross-validation for PC-Stable",
      "topics": [
        "pcCV"
      ]
    },
    {
      "page": "pcStable",
      "title": "Runs the causal discovery algorithm PC-Stable on a dataset.",
      "topics": [
        "pcStable"
      ]
    },
    {
      "page": "pcStars",
      "title": "Implements StARS for PC-Stable",
      "topics": [
        "pcStars"
      ]
    },
    {
      "page": "plot.graph",
      "title": "A plot override function for the graph class",
      "topics": [
        "plot.graph"
      ]
    },
    {
      "page": "plot.graphCV",
      "title": "A plot override function for the graphCV class",
      "topics": [
        "plot.graphCV"
      ]
    },
    {
      "page": "plot.graphPath",
      "title": "A plot override function for the graphPath class",
      "topics": [
        "plot.graphPath"
      ]
    },
    {
      "page": "plot.graphSTARS",
      "title": "A plot override function for the graphSTARS class",
      "topics": [
        "plot.graphSTARS"
      ]
    },
    {
      "page": "plot.graphSTEPS",
      "title": "A plot override function for the graphSTEPS class",
      "topics": [
        "plot.graphSTEPS"
      ]
    },
    {
      "page": "print.graph",
      "title": "A print override function for the graph class",
      "topics": [
        "print.graph"
      ]
    },
    {
      "page": "print.graphCV",
      "title": "A print override function for the graphCV class",
      "topics": [
        "print.graphCV"
      ]
    },
    {
      "page": "print.graphPath",
      "title": "A print override function for the graphPath class",
      "topics": [
        "print.graphPath"
      ]
    },
    {
      "page": "print.graphSTARS",
      "title": "A print override function for the graphSTARS class",
      "topics": [
        "print.graphSTARS"
      ]
    },
    {
      "page": "print.graphSTEPS",
      "title": "A print override function for the graphSTEPS class",
      "topics": [
        "print.graphSTEPS"
      ]
    },
    {
      "page": "print.knowledge",
      "title": "A print override function for the knowledge class",
      "topics": [
        "print.knowledge"
      ]
    },
    {
      "page": "printGraph",
      "title": "Display a graph object as text.",
      "topics": [
        "printGraph"
      ]
    },
    {
      "page": "prMetrics",
      "title": "Combined adjaceny and orientation precision-recall metrics",
      "topics": [
        "prMetrics"
      ]
    },
    {
      "page": "prMetricsAdjacency",
      "title": "Adjacency Precision-Recall Metrics",
      "topics": [
        "prMetricsAdjacency"
      ]
    },
    {
      "page": "prMetricsCausal",
      "title": "Causal Orientaion Precision-Recall Metrics for CPDAGs",
      "topics": [
        "prMetricsCausal"
      ]
    },
    {
      "page": "prMetricsOrientation",
      "title": "Orientation Precision-Recall Metrics",
      "topics": [
        "prMetricsOrientation"
      ]
    },
    {
      "page": "saveGraph",
      "title": "Save a graph to a file. Supported file types are \".txt\" and \".sif\".",
      "topics": [
        "saveGraph"
      ]
    },
    {
      "page": "SHD",
      "title": "Structural Hamming Distance (SHD)",
      "topics": [
        "SHD"
      ]
    },
    {
      "page": "simRandomDAG",
      "title": "A function to simulate a random forward DAG from a SEM model.",
      "topics": [
        "simRandomDAG"
      ]
    },
    {
      "page": "skeleton",
      "title": "Calculate the undirected skeleton for a given DAG",
      "topics": [
        "skeleton"
      ]
    },
    {
      "page": "steps",
      "title": "Implements StEPS and StARS for MGM",
      "topics": [
        "steps"
      ]
    }
  ],
  "_readme": "https://github.com/cran/rCausalMGM/raw/HEAD/README.md",
  "_rundeps": [
    "BH",
    "lattice",
    "Matrix",
    "Rcpp",
    "RcppArmadillo",
    "RcppThread",
    "survival"
  ],
  "_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"
    },
    {
      "shlib": "libgomp",
      "package": "libgomp1",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "openmp",
      "homepage": "http://gcc.gnu.org/",
      "description": "GCC OpenMP (GOMP) support library"
    }
  ],
  "_score": 2.3979400086720375,
  "_indexed": true,
  "_nocasepkg": "rcausalmgm",
  "_universes": [
    "cran"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "1.0.1",
      "date": "2026-05-12T09:21:22.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
      "fileid": "77b36cc6e817f931e11684d4f75eecedc13d22a9860422da8cc5434121845dec",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/25724886459"
    },
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "1.0.1",
      "date": "2026-05-12T09:21:53.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
      "fileid": "fd0f047dd4c672d33ced8a337c75a00f9e7f33c2995a3e6a512f1ad89f5b33f0",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/25724886459"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "1.0.1",
      "date": "2026-05-12T09:22:14.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
      "fileid": "5f65f9f037670ea98626504c5759375ba4d518d856597318e3ca81cce0f3958f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/25724886459"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "1.0.1",
      "date": "2026-05-12T09:21:27.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
      "fileid": "57f210933710943aa95e3bbcfc1f63ee335f719a2b5aa1208ac1e64cb70889eb",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/25724886459"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "1.0.1",
      "date": "2026-05-22T10:32:36.000Z",
      "arch": "emscripten",
      "commit": "9e0101244c379a33a1329dfdcb6b9ffcb01fb0d4",
      "fileid": "a57b2f09afeb99dccaf6b56ace59b0a9e61583c6966fea4b5e5160a58f52c95f",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/25724886459"
    }
  ]
}