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  "Title": "Fast Probabilistic Record Linkage with Missing Data",
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  "Date": "2023-11-17",
  "Authors@R": "c(\nperson(\"Ted\", \"Enamorado\", email = \"ted.enamorado@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Ben\", \"Fifield\", email = \"benfifield@gmail.com\", role = c(\"aut\")),\nperson(\"Kosuke\", \"Imai\", email = \"imai@harvard.edu\", role = c(\"aut\"))\n)",
  "Description": "Implements a Fellegi-Sunter probabilistic record linkage\nmodel that allows for missing data and the inclusion of\nauxiliary information. This includes functionalities to conduct\na merge of two datasets under the Fellegi-Sunter model using\nthe Expectation-Maximization algorithm. In addition, tools for\npreparing, adjusting, and summarizing data merges are included.\nThe package implements methods described in Enamorado, Fifield,\nand Imai (2019) ''Using a Probabilistic Model to Assist Merging\nof Large-scale Administrative Records''\n<doi:10.1017/S0003055418000783> and is available at\n<https://imai.fas.harvard.edu/research/linkage.html>.",
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  "Maintainer": "Ted Enamorado <ted.enamorado@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
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    "matchesLink",
    "nameReweight",
    "preprocText",
    "stringSubset",
    "tableCounts"
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    }
  ]
}