{
  "_id": "6a1025b9acfb0bcc41c8edd0",
  "Package": "sbm",
  "Title": "Stochastic Blockmodels",
  "Version": "0.4.7",
  "Authors@R": "c(person(given = \"Julien\", family = \"Chiquet\", role = c(\"aut\", \"cre\"),\nemail = \"julien.chiquet@inrae.fr\",\ncomment = c(ORCID = \"0000-0002-3629-3429\")),\nperson(given = \"Sophie\", family = \"Donnet\", role = c(\"aut\"),\nemail = \"sophie.donnet@inrae.fr\",\ncomment = c(ORCID = \"0000-0003-4370-7316\")),\nperson(\"großBM team\", role = c(\"ctb\")),\nperson(given = \"Pierre\", family = \"Barbillon\", role = c(\"aut\"),\nemail = \"pierre.barbillon@agroparistech.fr\",\ncomment = c(ORCID = \"0000-0002-7766-7693\")))",
  "Description": "A collection of tools and functions to adjust a variety of\nstochastic blockmodels (SBM). Supports at the moment Simple,\nBipartite, 'Multipartite' and Multiplex SBM (undirected or\ndirected with Bernoulli, Poisson or Gaussian emission laws on\nthe edges, and possibly covariate for Simple and Bipartite\nSBM). See Léger (2016) <doi:10.48550/arXiv.1602.07587>,\n'Barbillon et al.' (2020) <doi:10.1111/rssa.12193> and 'Bar-Hen\net al.' (2020) <doi:10.48550/arXiv.1807.10138>.",
  "URL": "https://grosssbm.github.io/sbm/",
  "BugReports": "https://github.com/GrossSBM/sbm/issues",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.2",
  "Language": "en-US",
  "Collate": "'R6Class-SBM.R' 'R6Class-BipartiteSBM.R'\n'R6Class-BipartiteSBM_fit.R' 'R6Class-MultipartiteSBM.R'\n'R6Class-MultipartiteSBM_fit.R' 'R6Class-MultiplexSBM_fit.R'\n'R6Class-SimpleSBM.R' 'R6Class-SimpleSBM_fit.R' 'RcppExports.R'\n'defineSBM.R' 'estimate.R' 'fungusTreeNetwork.R'\n'multipartiteEcologicalNetwork.R' 'plotAlluvial.R'\n'plotMyMatrix.R' 'plotMyMultipartiteMatrix.R'\n'plotMyMultiplexMatrix.R' 'sample.R' 'sbm-package.R'\n'utils-pipe.R' 'utils.R' 'utils_plot.R' 'war.R'",
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  "Config/pak/sysreqs": "libglpk-dev libicu-dev libxml2-dev",
  "Repository": "https://grosssbm.r-universe.dev",
  "Date/Publication": "2024-09-16 15:35:29 UTC",
  "RemoteUrl": "https://github.com/grosssbm/sbm",
  "RemoteRef": "HEAD",
  "RemoteSha": "a21af071ccff72c00c6bbb6894a8105921c5ab6c",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-05-13 09:20:20 UTC",
    "User": "root"
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  "Author": "Julien Chiquet [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-3629-3429>),\nSophie Donnet [aut] (ORCID: <https://orcid.org/0000-0003-4370-7316>),\ngroßBM team [ctb],\nPierre Barbillon [aut] (ORCID: <https://orcid.org/0000-0002-7766-7693>)",
  "Maintainer": "Julien Chiquet <julien.chiquet@inrae.fr>",
  "MD5sum": "1ecf45c04305536190300ea06d9975e3",
  "_user": "grosssbm",
  "_type": "src",
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  "_created": "2026-05-13T09:20:20.000Z",
  "_published": "2026-05-22T09:45:29.502Z",
  "_distro": "noble",
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    "author": "Julien Chiquet <julien.chiquet@inrae.fr>",
    "committer": "Julien Chiquet <julien.chiquet@inrae.fr>",
    "message": "CRAN resubmission\n",
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  "_usedby": 2,
  "_updates": [],
  "_tags": [],
  "_topics": [
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  ],
  "_stars": 17,
  "_contributors": [
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    "name": "GroßBM",
    "description": "A team to build damn outstanding packages to adjust a variety of stochastic blockmodels"
  },
  "_downloads": {
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/sbm"
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  "_devurl": "https://github.com/grosssbm/sbm",
  "_pkgdown": "https://grosssbm.github.io/sbm/",
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  "_rbuild": "4.6.0",
  "_assets": [
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    "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/sbm.html",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/grosssbm/sbm",
  "_realowner": "grosssbm",
  "_cranurl": true,
  "_releases": [
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      "version": "0.2.0",
      "date": "2020-07-07"
    },
    {
      "version": "0.2.1",
      "date": "2020-07-17"
    },
    {
      "version": "0.2.2",
      "date": "2020-10-12"
    },
    {
      "version": "0.4.1",
      "date": "2021-05-21"
    },
    {
      "version": "0.4.2",
      "date": "2021-05-31"
    },
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      "version": "0.4.3",
      "date": "2021-06-09"
    },
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      "version": "0.4.4",
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    },
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      "date": "2024-01-31"
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      "date": "2024-09-16"
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  "_exports": [
    "%>%",
    "BipartiteSBM",
    "BipartiteSBM_fit",
    "defineSBM",
    "estimateBipartiteSBM",
    "estimateMultipartiteSBM",
    "estimateMultiplexSBM",
    "estimateSimpleSBM",
    "is_SBM",
    "MultipartiteSBM",
    "MultipartiteSBM_fit",
    "MultiplexSBM_fit",
    "plotAlluvial",
    "plotMyMatrix",
    "plotMyMultipartiteMatrix",
    "plotMyMultiplexMatrix",
    "sampleBipartiteSBM",
    "sampleMultipartiteSBM",
    "sampleMultiplexSBM",
    "sampleSimpleSBM",
    "SimpleSBM",
    "SimpleSBM_fit"
  ],
  "_datasets": [
    {
      "name": "fungusTreeNetwork",
      "title": "fungus-tree interaction network",
      "object": "fungusTreeNetwork",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "multipartiteEcologicalNetwork",
      "title": "Ecological multipartite interaction network",
      "object": "multipartiteEcologicalNetwork",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "war",
      "title": "War data set",
      "object": "war",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
  ],
  "_help": [
    {
      "page": "BipartiteSBM",
      "title": "R6 class for Bipartite SBM",
      "topics": [
        "BipartiteSBM"
      ]
    },
    {
      "page": "BipartiteSBM_fit",
      "title": "R6 Class definition of an Bipartite SBM fit",
      "topics": [
        "BipartiteSBM_fit"
      ]
    },
    {
      "page": "coef.SBM",
      "title": "Extract model coefficients",
      "topics": [
        "coef.SBM"
      ]
    },
    {
      "page": "defineSBM",
      "title": "Define a network",
      "topics": [
        "defineSBM"
      ]
    },
    {
      "page": "estimateBipartiteSBM",
      "title": "Estimation of Bipartite SBMs",
      "topics": [
        "estimateBipartiteSBM"
      ]
    },
    {
      "page": "estimateMultipartiteSBM",
      "title": "Estimation for multipartite SBM",
      "topics": [
        "estimateMultipartiteSBM"
      ]
    },
    {
      "page": "estimateMultiplexSBM",
      "title": "Estimation for Multiplex SBM",
      "topics": [
        "estimateMultiplexSBM"
      ]
    },
    {
      "page": "estimateSimpleSBM",
      "title": "Estimation of Simple SBMs",
      "topics": [
        "estimateSimpleSBM"
      ]
    },
    {
      "page": "fitted.SBM",
      "title": "Extract model fitted values",
      "topics": [
        "fitted.SBM"
      ]
    },
    {
      "page": "fungusTreeNetwork",
      "title": "fungus-tree interaction network",
      "topics": [
        "fungusTreeNetwork"
      ]
    },
    {
      "page": "is_SBM",
      "title": "Auxiliary function to check the given class of an object",
      "topics": [
        "is_SBM"
      ]
    },
    {
      "page": "multipartiteEcologicalNetwork",
      "title": "Ecological multipartite interaction network",
      "topics": [
        "multipartiteEcologicalNetwork"
      ]
    },
    {
      "page": "MultipartiteSBM",
      "title": "R6 Class definition of a Multipartite SBM",
      "topics": [
        "MultipartiteSBM"
      ]
    },
    {
      "page": "MultipartiteSBM_fit",
      "title": "R6 Class definition of a Multipartite SBM fit",
      "topics": [
        "MultipartiteSBM_fit"
      ]
    },
    {
      "page": "MultiplexSBM_fit",
      "title": "R6 Class definition of a Multiplex SBM fit",
      "topics": [
        "MultiplexSBM_fit"
      ]
    },
    {
      "page": "plot.SBM",
      "title": "SBM Plot",
      "topics": [
        "plot.SBM"
      ]
    },
    {
      "page": "plotAlluvial",
      "title": "Plot an alluvial plot between clusterings",
      "topics": [
        "plotAlluvial"
      ]
    },
    {
      "page": "plotMyMatrix",
      "title": "Plot an adjacency or incidence Matrix",
      "topics": [
        "plotMyMatrix"
      ]
    },
    {
      "page": "plotMyMultipartiteMatrix",
      "title": "Plot the matrices corresponding to a Multipartite Network",
      "topics": [
        "plotMyMultipartiteMatrix"
      ]
    },
    {
      "page": "plotMyMultiplexMatrix",
      "title": "Plot the matrices corresponding to a Multiplex Network",
      "topics": [
        "plotMyMultiplexMatrix"
      ]
    },
    {
      "page": "predict.SBM",
      "title": "Model Predictions",
      "topics": [
        "predict.SBM"
      ]
    },
    {
      "page": "sampleBipartiteSBM",
      "title": "Sampling of Bipartite SBMs",
      "topics": [
        "sampleBipartiteSBM"
      ]
    },
    {
      "page": "sampleMultipartiteSBM",
      "title": "Sampling of Multipartite SBMs",
      "topics": [
        "sampleMultipartiteSBM"
      ]
    },
    {
      "page": "sampleMultiplexSBM",
      "title": "Sampling of Multiplex SBMs",
      "topics": [
        "sampleMultiplexSBM"
      ]
    },
    {
      "page": "sampleSimpleSBM",
      "title": "Sampling of Simple SBMs",
      "topics": [
        "sampleSimpleSBM"
      ]
    },
    {
      "page": "SBM",
      "title": "R6 virtual class for SBM representation (mother class of SimpleSBM, BipartiteSBM, MultipartiteSBM)",
      "topics": [
        "SBM"
      ]
    },
    {
      "page": "SimpleSBM",
      "title": "R6 class for Simple SBM",
      "topics": [
        "SimpleSBM"
      ]
    },
    {
      "page": "SimpleSBM_fit",
      "title": "R6 Class definition of a Simple SBM fit",
      "topics": [
        "SimpleSBM_fit"
      ]
    },
    {
      "page": "war",
      "title": "War data set",
      "topics": [
        "war"
      ]
    }
  ],
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  "_vignettes": [
    {
      "source": "Multipartite_EcologicalNetwork.Rmd",
      "filename": "Multipartite_EcologicalNetwork.html",
      "title": "Multipartite Stochastic Block Models",
      "author": "team großBM",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Preliminaries",
        "Requirements",
        "Dataset",
        "Formatting the data",
        "Mathematical Background",
        "Inference",
        "Plots",
        "References"
      ],
      "created": "2020-12-18 08:44:22",
      "modified": "2022-09-12 10:11:24",
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    {
      "source": "SBM_fungus_tree_network.Rmd",
      "filename": "SBM_fungus_tree_network.html",
      "title": "Simple and Bipartite Stochastic Block Models",
      "author": "team großBM",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Preliminaries",
        "Requirements",
        "Data set: antagonistic tree/fungus interaction network",
        "Mathematical Background",
        "Analysis of the tree/tree data",
        "Tree-tree binary interaction networks",
        "About model selection and choice of the number of blocks",
        "Analysis of the weighted interaction network",
        "Introduction of covariates",
        "Analysis of the tree/fungi data",
        "References"
      ],
      "created": "2020-06-25 13:19:28",
      "modified": "2022-09-12 10:11:24",
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    },
    {
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      "filename": "Multiplex_allianceNwar_case_study.html",
      "title": "Stochastic Block Models for Multiplex networks",
      "author": "team großBM",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Preliminaries",
        "Requirements",
        "Data set",
        "Data manipulation",
        "Fitting a multiplex SBM model where the two layers are assumed to be independent",
        "Fitting a multiplex SBM model where the two layers are assumed to be dependent",
        "References"
      ],
      "created": "2021-05-19 14:05:14",
      "modified": "2023-01-07 06:39:26",
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    },
    {
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      "filename": "MultiplexNetwork_principle.html",
      "title": "Stochastic Block Models for Multiplex networks",
      "author": "team großBM",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Preliminaries",
        "Requirements",
        "Multiplex network data",
        "Stochastic Block models for multiplex networks",
        "General formulation of the model",
        "Dependent and independent layers conditionally to $Z$",
        "Bipartite multiplex networks",
        "Inference",
        "Implementation",
        "Data simulation",
        "References"
      ],
      "created": "2021-05-05 17:06:18",
      "modified": "2022-09-12 10:11:24",
      "commits": 6
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