{
  "_id": "6a1ffaf6b401979e734448f5",
  "Package": "MEDseq",
  "Type": "Package",
  "Date": "2025-03-10",
  "Title": "Mixtures of Exponential-Distance Models with Covariates",
  "Version": "1.4.2",
  "Authors@R": "c(person(\"Keefe\", \"Murphy\", email = \"keefe.murphy@mu.ie\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-7709-3159\")),\nperson(\"Thomas Brendan\", \"Murphy\", email = \"brendan.murphy@ucd.ie\", role = \"ctb\", comment = c(ORCID = \"0000-0002-5668-7046\")),\nperson(\"Raffaella\", \"Piccarreta\", email = \"raffaella.piccarreta@unibocconi.it \", role = \"ctb\", comment = c(ORCID = \"0000-0002-8876-3656\")),\nperson(\"Isobel Claire\", \"Gormley\", email = \"claire.gormley@ucd.ie\", role = \"ctb\", comment = c(ORCID = \"0000-0001-7713-681X\")))",
  "Description": "Implements a model-based clustering method for categorical\nlife-course sequences relying on mixtures of\nexponential-distance models introduced by Murphy et al. (2021)\n<doi:10.1111/rssa.12712>. A range of flexible precision\nparameter settings corresponding to weighted generalisations of\nthe Hamming distance metric are considered, along with the\npotential inclusion of a noise component. Gating covariates can\nbe supplied in order to relate sequences to baseline\ncharacteristics and sampling weights are also accommodated. The\nmodels are fitted using the EM algorithm and tools for\nvisualising the results are also provided.",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "URL": "https://cran.r-project.org/package=MEDseq",
  "BugReports": "https://github.com/Keefe-Murphy/MEDseq/issues",
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  "Language": "en-GB",
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  "Repository": "https://keefe-murphy.r-universe.dev",
  "Date/Publication": "2025-03-10 10:33:24 UTC",
  "RemoteUrl": "https://github.com/keefe-murphy/medseq",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-03 09:55:59 UTC",
    "User": "root"
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  "Author": "Keefe Murphy [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-7709-3159>),\nThomas Brendan Murphy [ctb] (ORCID:\n<https://orcid.org/0000-0002-5668-7046>),\nRaffaella Piccarreta [ctb] (ORCID:\n<https://orcid.org/0000-0002-8876-3656>),\nIsobel Claire Gormley [ctb] (ORCID:\n<https://orcid.org/0000-0001-7713-681X>)",
  "Maintainer": "Keefe Murphy <keefe.murphy@mu.ie>",
  "MD5sum": "6e6ae672694d6fd24e34eccf1b930678",
  "_user": "keefe-murphy",
  "_type": "src",
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  "_created": "2026-06-03T09:55:59.000Z",
  "_published": "2026-06-03T09:59:18.742Z",
  "_distro": "noble",
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    "author": "Keefe-Murphy <keefe.murphy@mu.ie>",
    "committer": "Keefe-Murphy <keefe.murphy@mu.ie>",
    "message": "Prepared CRAN release. Added Raffaella's ORCID ID & hidden function \".theta0\" for extracting the modal sequence of the noise component. print.MEDseq now works again for all models with G=1. dist.mat experimental feature now governs initialisation ONLY, no longer ASW calculations. Additional documentation clarifications & spell-checking.\n",
    "time": 1741602804
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  "_maintainer": {
    "name": "Keefe Murphy",
    "email": "keefe.murphy@mu.ie",
    "login": "keefe-murphy",
    "orcid": "0000-0002-7709-3159",
    "description": "",
    "uuid": 15124488
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  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_topics": [
    "distance-based-clustering",
    "mixture-of-experts",
    "model-based-clustering",
    "sequence-analysis"
  ],
  "_stars": 5,
  "_contributors": [
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      "user": "keefe-murphy",
      "count": 23,
      "uuid": 15124488
    }
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  "_userbio": {
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    "type": "user",
    "name": "Keefe Murphy"
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  "_downloads": {
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/MEDseq"
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  "_devurl": "https://github.com/keefe-murphy/medseq",
  "_searchresults": 25,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/MEDseq.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/keefe-murphy/medseq",
  "_realowner": "keefe-murphy",
  "_cranurl": true,
  "_releases": [
    {
      "version": "1.0.0",
      "date": "2019-08-24"
    },
    {
      "version": "1.0.1",
      "date": "2019-12-11"
    },
    {
      "version": "1.1.0",
      "date": "2020-03-31"
    },
    {
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      "date": "2020-05-12"
    },
    {
      "version": "1.2.0",
      "date": "2020-11-21"
    },
    {
      "version": "1.2.1",
      "date": "2021-01-06"
    },
    {
      "version": "1.3.0",
      "date": "2021-07-15"
    },
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      "date": "2021-10-14"
    },
    {
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      "date": "2021-12-19"
    },
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      "version": "1.3.3",
      "date": "2022-03-28"
    },
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      "date": "2022-12-20"
    },
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      "version": "1.4.1",
      "date": "2023-12-12"
    },
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      "date": "2025-03-10"
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    "dist_freqwH",
    "get_MEDseq_results",
    "MEDseq_AvePP",
    "MEDseq_clustnames",
    "MEDseq_compare",
    "MEDseq_control",
    "MEDseq_entropy",
    "MEDseq_fit",
    "MEDseq_meantime",
    "MEDseq_nameclusts",
    "MEDseq_news",
    "MEDseq_stderr",
    "seqdef",
    "wKModes"
  ],
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      "title": "Family life states from the Swiss Household Panel biographical survey",
      "object": "biofam",
      "class": [
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      ],
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        "idhous",
        "sex",
        "birthyr",
        "nat_1_02",
        "plingu02",
        "p02r01",
        "p02r04",
        "cspfaj",
        "cspmoj",
        "a15",
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        "wp00tbgp",
        "wp00tbgs"
      ],
      "rows": 2000,
      "table": true,
      "tojson": true
    },
    {
      "name": "mvad",
      "title": "MVAD: Transition from school to work",
      "object": "mvad",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "weight",
        "male",
        "catholic",
        "Belfast",
        "N.Eastern",
        "Southern",
        "S.Eastern",
        "Western",
        "Grammar",
        "funemp",
        "gcse5eq",
        "fmpr",
        "livboth",
        "Jul.93",
        "Aug.93",
        "Sep.93",
        "Oct.93",
        "Nov.93",
        "Dec.93",
        "Jan.94",
        "Feb.94",
        "Mar.94",
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        "Jun.96",
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      ],
      "rows": 712,
      "table": true,
      "tojson": true
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  "_help": [
    {
      "page": "MEDseq-package",
      "title": "MEDseq: Mixtures of Exponential-Distance Models with Covariates",
      "topics": [
        "MEDseq-package",
        "MEDseq"
      ]
    },
    {
      "page": "biofam",
      "title": "Family life states from the Swiss Household Panel biographical survey",
      "topics": [
        "biofam"
      ]
    },
    {
      "page": "dbs",
      "title": "Compute the Density-based Silhouette",
      "topics": [
        "dbs"
      ]
    },
    {
      "page": "dist_freqwH",
      "title": "Pairwise frequency-Weighted Hamming distance matrix for categorical data",
      "topics": [
        "dist_freqwH"
      ]
    },
    {
      "page": "get_MEDseq_results",
      "title": "Extract results from a MEDseq model",
      "topics": [
        "get_MEDseq_results"
      ]
    },
    {
      "page": "MEDseq_AvePP",
      "title": "Average posterior probabilities of a fitted MEDseq model",
      "topics": [
        "MEDseq_AvePP"
      ]
    },
    {
      "page": "MEDseq_clustnames",
      "title": "Automatic labelling of clusters using central sequences",
      "topics": [
        "MEDseq_clustnames",
        "MEDseq_nameclusts"
      ]
    },
    {
      "page": "MEDseq_compare",
      "title": "Choose the best MEDseq model",
      "topics": [
        "MEDseq_compare",
        "print.MEDseqCompare"
      ]
    },
    {
      "page": "MEDseq_control",
      "title": "Set control values for use with MEDseq_fit",
      "topics": [
        "MEDseq_control"
      ]
    },
    {
      "page": "MEDseq_entropy",
      "title": "Entropy of a fitted MEDseq model",
      "topics": [
        "MEDseq_entropy"
      ]
    },
    {
      "page": "MEDseq_fit",
      "title": "MEDseq: Mixtures of Exponential-Distance Models with Covariates",
      "topics": [
        "MEDseq_fit",
        "print.MEDseq",
        "summary.MEDseq"
      ]
    },
    {
      "page": "MEDseq_meantime",
      "title": "Compute the mean time spent in each sequence category",
      "topics": [
        "MEDseq_meantime",
        "print.MEDseqMeanTime"
      ]
    },
    {
      "page": "MEDseq_news",
      "title": "Show the NEWS file",
      "topics": [
        "MEDseq_news"
      ]
    },
    {
      "page": "MEDseq_stderr",
      "title": "MEDseq gating network standard errors",
      "topics": [
        "MEDseq_stderr"
      ]
    },
    {
      "page": "mvad",
      "title": "MVAD: Transition from school to work",
      "topics": [
        "mvad"
      ]
    },
    {
      "page": "plot.MEDseq",
      "title": "Plot MEDseq results",
      "topics": [
        "plot.MEDseq"
      ]
    },
    {
      "page": "predict.MEDgating",
      "title": "Predictions from MEDseq gating networks",
      "topics": [
        "fitted.MEDgating",
        "predict.MEDgating",
        "residuals.MEDgating"
      ]
    },
    {
      "page": "wKModes",
      "title": "Weighted K-Modes Clustering with Tie-Breaking",
      "topics": [
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    }
  ]
}