{
  "_id": "6a10045facfb0bcc41c7d881",
  "Package": "SparseMSE",
  "Title": "'Multiple Systems Estimation for Sparse Capture Data'",
  "Version": "3.0.1",
  "Authors@R": "c(\nperson(\"Lax\", \"Chan\", email = \"laxchan77@gmail.com\", role = c(\"aut\",\"cre\")),\nperson(\"Bernard\", \"Silverman\", email = \"mail@bernardsilverman.co.uk\", role = c(\"aut\")),\nperson(\"Kyle\", \"Vincent\", email = \"kyle.shane.vincent@gmail.com\", role= c(\"aut\")))",
  "Author": "Lax Chan [aut, cre], Bernard Silverman [aut], Kyle Vincent\n[aut]",
  "Maintainer": "Lax Chan <laxchan77@gmail.com>",
  "Description": "Implements the routines and algorithms developed and\nanalysed in \"Multiple Systems Estimation for Sparse Capture\nData: Inferential Challenges when there are Non-Overlapping\nLists\" Chan, L, Silverman, B. W., Vincent, K (2019)\n<https://www.tandfonline.com/doi/full/10.1080/01621459.2019.1708748>\nand in \"Bootstrapping multiple systems estimates to account for\nmodel selection\" Silverman, B. W., Chan, L, Vincent, K\n(2023)<https://doi.org/10.1007/s11222-023-10346-9>. This\npackage explicitly handles situations where there are pairs of\nlists which have no observed individuals in common.  It deals\ncorrectly with parameters whose estimated values can be\nconsidered as being negative infinity.  It also addresses other\npossible issues of non-existence and non-identifiability of\nmaximum likelihood estimates.",
  "URL": "https://www.tandfonline.com/doi/full/10.1080/01621459.2019.1708748\nhttps://doi.org/10.1007/s11222-023-10346-9",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.2.3",
  "Repository": "https://laxchan.r-universe.dev",
  "Date/Publication": "2024-01-08 22:18:50 UTC",
  "RemoteUrl": "https://github.com/laxchan/sparsemse",
  "RemoteRef": "HEAD",
  "RemoteSha": "627b8bbb2e9b545e9a14f0d355ba96111d960fc3",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-22 07:20:13 UTC",
    "User": "root"
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  "MD5sum": "30fccf7ee930fc299e09443a115c11db",
  "_user": "laxchan",
  "_type": "src",
  "_file": "SparseMSE_3.0.1.tar.gz",
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  "_created": "2026-05-22T07:20:13.000Z",
  "_published": "2026-05-22T07:23:11.534Z",
  "_distro": "noble",
  "_jobs": [
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  "_buildurl": "https://github.com/r-universe/laxchan/actions/runs/26274088793",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/laxchan/sparsemse",
  "_commit": {
    "id": "627b8bbb2e9b545e9a14f0d355ba96111d960fc3",
    "author": "Laxchan <34035463+Laxchan@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Add files via upload",
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    "email": "laxchan77@gmail.com",
    "login": "laxchan",
    "description": "",
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  "_registered": true,
  "_dependencies": [
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      "package": "R",
      "version": ">= 4.2.0",
      "role": "Depends"
    },
    {
      "package": "lpSolve",
      "role": "Imports"
    },
    {
      "package": "Rcapture",
      "role": "Imports"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "laxchan",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
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    "type": "user",
    "name": "Laxchan"
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  "_downloads": {
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/SparseMSE"
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  "_devurl": "https://github.com/laxchan/sparsemse",
  "_searchresults": 7,
  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/SparseMSE.html",
    "manual.pdf"
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  "_homeurl": "https://github.com/laxchan/sparsemse",
  "_realowner": "laxchan",
  "_cranurl": true,
  "_releases": [
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      "version": "1.2.1",
      "date": "2019-03-05"
    },
    {
      "version": "2.0.0",
      "date": "2019-12-01"
    },
    {
      "version": "2.0.1",
      "date": "2019-12-15"
    }
  ],
  "_exports": [
    "ancestors",
    "assemble_bic",
    "bcaconfvalues",
    "BICandbootstrapsim",
    "bicktopahatcal",
    "BICrank_tiebreak",
    "bootstrap_mse",
    "bootstrapcal",
    "boundary_captures",
    "buildmodel",
    "buildmodelmatrix",
    "checkallmodels",
    "checkident",
    "checkident.1",
    "checkident.2",
    "checkthetasubset",
    "child_captures",
    "convert_from_hierarchy",
    "convert_to_hierarchy",
    "count_triples",
    "decode_capture",
    "descendants",
    "downhill_bootstrapcal",
    "downhill_fit",
    "downhill_funs",
    "downhill_jackknifecal",
    "encode_capture",
    "estimatepopulation",
    "estimatepopulation.0",
    "find_bic_rank_matrix",
    "find_neighbour_hierarchies",
    "find_unique_patterns",
    "fit_hier_model",
    "gethiermodels",
    "ingest_data",
    "investigateAIC",
    "jackknifecal",
    "ktopBCa",
    "make_master_design",
    "modelfit",
    "modelorder",
    "ntopBCa",
    "ordercaptures",
    "parent_captures",
    "removenoninformativelists",
    "stepwisefit",
    "subsetmat",
    "subsetsearch",
    "tidylists"
  ],
  "_datasets": [
    {
      "name": "Artificial_3",
      "title": "Artificial data set to demonstrate possible instabilities",
      "object": "Artificial_3",
      "class": [
        "data.frame"
      ],
      "fields": [
        "A",
        "B",
        "C",
        "n"
      ],
      "rows": 4,
      "table": true,
      "tojson": true
    },
    {
      "name": "hiermodels",
      "title": "Hierarchical models",
      "object": "hiermodels",
      "class": [
        "character"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "Korea",
      "title": "Korea data",
      "object": "Korea",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "b",
        "c",
        "d",
        "Count"
      ],
      "rows": 7,
      "table": true,
      "tojson": true
    },
    {
      "name": "Kosovo",
      "title": "Kosovo data",
      "object": "Kosovo",
      "class": [
        "data.frame"
      ],
      "fields": [
        "EXH",
        "ABA",
        "OSCE",
        "HRW",
        "Frequency"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "Ned",
      "title": "The Netherlands data",
      "object": "Ned",
      "class": [
        "data.frame"
      ],
      "fields": [
        "I",
        "K",
        "O",
        "P",
        "R",
        "Z",
        "frequency"
      ],
      "rows": 24,
      "table": true,
      "tojson": true
    },
    {
      "name": "Ned_5",
      "title": "Netherlands data five list version",
      "object": "Ned_5",
      "class": [
        "data.frame"
      ],
      "fields": [
        "IO",
        "K",
        "P",
        "R",
        "Z",
        "frequency"
      ],
      "rows": 17,
      "table": true,
      "tojson": true
    },
    {
      "name": "NewOrl",
      "title": "New Orleans data",
      "object": "NewOrl",
      "class": [
        "data.frame"
      ],
      "fields": [
        "A",
        "B",
        "C",
        "D",
        "E",
        "F",
        "G",
        "H",
        "n"
      ],
      "rows": 19,
      "table": true,
      "tojson": true
    },
    {
      "name": "NewOrl_5",
      "title": "New Orleans data five list version",
      "object": "NewOrl_5",
      "class": [
        "data.frame"
      ],
      "fields": [
        "A",
        "BEFG",
        "C",
        "D",
        "H",
        "n"
      ],
      "rows": 14,
      "table": true,
      "tojson": true
    },
    {
      "name": "UKdat",
      "title": "UK data",
      "object": "UKdat",
      "class": [
        "data.frame"
      ],
      "fields": [
        "LA",
        "NG",
        "PF",
        "GO",
        "GP",
        "NCA",
        "count"
      ],
      "rows": 25,
      "table": true,
      "tojson": true
    },
    {
      "name": "UKdat_5",
      "title": "UK data five list version",
      "object": "UKdat_5",
      "class": [
        "data.frame"
      ],
      "fields": [
        "LA",
        "NG",
        "PFNCA",
        "GO",
        "GP",
        "count"
      ],
      "rows": 18,
      "table": true,
      "tojson": true
    },
    {
      "name": "Western",
      "title": "Victims related to sex trafficking in a U.S. Western site",
      "object": "Western",
      "class": [
        "data.frame"
      ],
      "fields": [
        "A",
        "B",
        "C",
        "D",
        "E",
        "n"
      ],
      "rows": 13,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "ancestors",
      "title": "Find the \"ancestors\" of a given capture history",
      "topics": [
        "ancestors"
      ]
    },
    {
      "page": "Artificial_3",
      "title": "Artificial data set to demonstrate possible instabilities",
      "topics": [
        "Artificial_3"
      ]
    },
    {
      "page": "assemble_bic",
      "title": "Models BICS, abundance and maxorder.",
      "topics": [
        "assemble_bic"
      ]
    },
    {
      "page": "bcaconfvalues",
      "title": "BCa confidence intervals",
      "topics": [
        "bcaconfvalues"
      ]
    },
    {
      "page": "BICandbootstrapsim",
      "title": "Comparison of BIC approach and BCa approach",
      "topics": [
        "BICandbootstrapsim"
      ]
    },
    {
      "page": "bicktopahatcal",
      "title": "Acceleration factor calculation",
      "topics": [
        "bicktopahatcal"
      ]
    },
    {
      "page": "BICrank_tiebreak",
      "title": "Return a BIC rank matrix breaking ties with each roles",
      "topics": [
        "BICrank_tiebreak"
      ]
    },
    {
      "page": "bootstrap_mse",
      "title": "A routine for naive user",
      "topics": [
        "bootstrap_mse"
      ]
    },
    {
      "page": "bootstrapcal",
      "title": "Bootstrap abundance and bic",
      "topics": [
        "bootstrapcal"
      ]
    },
    {
      "page": "boundary_captures",
      "title": "Given a vector of captures, find those which are not in the vector but all of whose parents are",
      "topics": [
        "boundary_captures"
      ]
    },
    {
      "page": "buildmodel",
      "title": "Build model for multiple systems estimation",
      "topics": [
        "buildmodel"
      ]
    },
    {
      "page": "buildmodelmatrix",
      "title": "Build the model matrix based on particular data, as required to check for identifiability and existence of the maximum likelihood estimate",
      "topics": [
        "buildmodelmatrix"
      ]
    },
    {
      "page": "checkallmodels",
      "title": "Check all possible models for existence and identifiability",
      "topics": [
        "checkallmodels"
      ]
    },
    {
      "page": "checkident",
      "title": "Check a model for the existence and identifiability of the maximum likelihood estimate",
      "topics": [
        "checkident"
      ]
    },
    {
      "page": "checkident.1",
      "title": "The Fienberg-Rinaldo linear program check for the existence of the estimates",
      "topics": [
        "checkident.1"
      ]
    },
    {
      "page": "checkident.2",
      "title": "Carry out the Fienberg-Rinaldo procedure on an array of data vectors and a vector of models",
      "topics": [
        "checkident.2"
      ]
    },
    {
      "page": "checkthetasubset",
      "title": "Check a subset of the parameter set theta",
      "topics": [
        "checkthetasubset"
      ]
    },
    {
      "page": "child_captures",
      "title": "Find the \"children\" of a given capture history",
      "topics": [
        "child_captures"
      ]
    },
    {
      "page": "convert_from_hierarchy",
      "title": "Find the vector of captures corresponding to a given hierarchical model",
      "topics": [
        "convert_from_hierarchy"
      ]
    },
    {
      "page": "convert_to_hierarchy",
      "title": "Find hierarchical representation of a vector of captures",
      "topics": [
        "convert_to_hierarchy"
      ]
    },
    {
      "page": "count_triples",
      "title": "Count number of triples of overlapping lists",
      "topics": [
        "count_triples"
      ]
    },
    {
      "page": "decode_capture",
      "title": "Decode capture history",
      "topics": [
        "decode_capture"
      ]
    },
    {
      "page": "descendants",
      "title": "Find the \"descendants\" of a given capture history",
      "topics": [
        "descendants"
      ]
    },
    {
      "page": "downhill_bootstrapcal",
      "title": "Bootstrap downhill",
      "topics": [
        "downhill_bootstrapcal"
      ]
    },
    {
      "page": "downhill_fit",
      "title": "Conduct downhill search among hierarchical models starting from the main effects only.",
      "topics": [
        "downhill_fit"
      ]
    },
    {
      "page": "downhill_funs",
      "title": "Downhill wrapper",
      "topics": [
        "downhill_funs"
      ]
    },
    {
      "page": "downhill_jackknifecal",
      "title": "Jackknife downhill",
      "topics": [
        "downhill_jackknifecal"
      ]
    },
    {
      "page": "encode_capture",
      "title": "Encode capture history",
      "topics": [
        "encode_capture"
      ]
    },
    {
      "page": "estimatepopulation",
      "title": "Bootstrapping to evaluate confidence intervals using BCa methods",
      "topics": [
        "estimatepopulation"
      ]
    },
    {
      "page": "estimatepopulation.0",
      "title": "Estimate the total population including the dark figure.  If the user wishes to find bootstrap confidence intervals then the routine 'estimatepopulation' should be used instead.",
      "topics": [
        "estimatepopulation.0"
      ]
    },
    {
      "page": "find_bic_rank_matrix",
      "title": "Find BIC rank matrix up to a specified number of bic ranks for a given data set",
      "topics": [
        "find_bic_rank_matrix"
      ]
    },
    {
      "page": "find_neighbour_hierarchies",
      "title": "Find all neighbouring hierarchical model to a given one",
      "topics": [
        "find_neighbour_hierarchies"
      ]
    },
    {
      "page": "find_unique_patterns",
      "title": "Find unique patterns in matrix columns",
      "topics": [
        "find_unique_patterns"
      ]
    },
    {
      "page": "fit_hier_model",
      "title": "Fit a hierarchical model taking account of possible sparsity",
      "topics": [
        "fit_hier_model"
      ]
    },
    {
      "page": "gethiermodels",
      "title": "Get a list of all hierarchical models for given number of lists and maximum order",
      "topics": [
        "gethiermodels"
      ]
    },
    {
      "page": "hiermodels",
      "title": "Hierarchical models",
      "topics": [
        "hiermodels"
      ]
    },
    {
      "page": "ingest_data",
      "title": "Preliminary processing of a data matrix",
      "topics": [
        "ingest_data"
      ]
    },
    {
      "page": "investigateAIC",
      "title": "Plot of simulation study",
      "topics": [
        "investigateAIC"
      ]
    },
    {
      "page": "jackknifecal",
      "title": "Jackknife abundance and Jackknife bic",
      "topics": [
        "jackknifecal"
      ]
    },
    {
      "page": "Korea",
      "title": "Korea data",
      "topics": [
        "Korea"
      ]
    },
    {
      "page": "Kosovo",
      "title": "Kosovo data",
      "topics": [
        "Kosovo"
      ]
    },
    {
      "page": "ktopBCa",
      "title": "Find BCa confidence intervals using ktop idea.",
      "topics": [
        "ktopBCa"
      ]
    },
    {
      "page": "make_master_design",
      "title": "Set up the inclusion matrix for all possible capture histories",
      "topics": [
        "make_master_design"
      ]
    },
    {
      "page": "modelfit",
      "title": "Fit a specified model to multiple systems estimation data",
      "topics": [
        "modelfit"
      ]
    },
    {
      "page": "modelorder",
      "title": "Order of models",
      "topics": [
        "modelorder"
      ]
    },
    {
      "page": "Ned",
      "title": "The Netherlands data",
      "topics": [
        "Ned"
      ]
    },
    {
      "page": "Ned_5",
      "title": "Netherlands data five list version",
      "topics": [
        "Ned_5"
      ]
    },
    {
      "page": "NewOrl",
      "title": "New Orleans data",
      "topics": [
        "NewOrl"
      ]
    },
    {
      "page": "NewOrl_5",
      "title": "New Orleans data five list version",
      "topics": [
        "NewOrl_5"
      ]
    },
    {
      "page": "ntopBCa",
      "title": "Find BCa confidence intervals for all possible ntop",
      "topics": [
        "ntopBCa"
      ]
    },
    {
      "page": "ordercaptures",
      "title": "Order capture histories",
      "topics": [
        "ordercaptures"
      ]
    },
    {
      "page": "parent_captures",
      "title": "Find the \"parents\" of a given capture history",
      "topics": [
        "parent_captures"
      ]
    },
    {
      "page": "removenoninformativelists",
      "title": "Remove non-informative list",
      "topics": [
        "removenoninformativelists"
      ]
    },
    {
      "page": "sortmodelsbic",
      "title": "Models BICS, abundance and maxorder.",
      "topics": [
        "sortmodelsbic"
      ]
    },
    {
      "page": "stepwisefit",
      "title": "Stepwise fit using Poisson p-values.",
      "topics": [
        "stepwisefit"
      ]
    },
    {
      "page": "subsetmat",
      "title": "Subset matrix",
      "topics": [
        "subsetmat"
      ]
    },
    {
      "page": "subsetsearch",
      "title": "Search subsets for a property which is inherited in a particular way",
      "topics": [
        "subsetsearch"
      ]
    },
    {
      "page": "tidylists",
      "title": "Produce a data matrix with a unique row for each capture history",
      "topics": [
        "tidylists"
      ]
    },
    {
      "page": "UKdat",
      "title": "UK data",
      "topics": [
        "UKdat"
      ]
    },
    {
      "page": "UKdat_5",
      "title": "UK data five list version",
      "topics": [
        "UKdat_5"
      ]
    },
    {
      "page": "Western",
      "title": "Victims related to sex trafficking in a U.S. Western site",
      "topics": [
        "Western"
      ]
    }
  ],
  "_rundeps": [
    "lpSolve",
    "Rcapture"
  ],
  "_score": 2,
  "_indexed": true,
  "_nocasepkg": "sparsemse",
  "_universes": [
    "laxchan"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
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