{
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  "Package": "ebal",
  "Type": "Package",
  "Title": "Entropy Reweighting to Create Balanced Samples",
  "Version": "0.3-0",
  "Date": "2026-05-04",
  "Authors@R": "c(\nperson(\"Jens\", \"Hainmueller\", email = \"jhain@stanford.edu\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Apoorva\", \"Lal\", email = \"lal.apoorva@gmail.com\",\nrole = \"aut\",\ncomment = \"torch-based autodiff solver (R/ebalance_autodiff.R)\"))",
  "Description": "Implements entropy balancing, a data preprocessing\nprocedure described in Hainmueller (2012,\n<doi:10.1093/pan/mpr025>) that allows users to reweight a\ndataset such that the covariate distributions in the reweighted\ndata satisfy a set of user-specified moment conditions. Useful\nfor creating balanced samples in observational studies with a\nbinary treatment where the control group is reweighted to match\nthe covariate moments of the treatment group, and for\nreweighting a survey sample to known characteristics from a\ntarget population.",
  "License": "GPL (>= 2)",
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  "VignetteBuilder": "knitr",
  "URL": "https://web.stanford.edu/~jhain/, https://github.com/j-hai/ebal",
  "BugReports": "https://github.com/j-hai/ebal/issues",
  "Encoding": "UTF-8",
  "Repository": "https://j-hai.r-universe.dev",
  "Date/Publication": "2026-05-12 17:55:52 UTC",
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    "User": "root"
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  "Author": "Jens Hainmueller [aut, cre],\nApoorva Lal [aut] (torch-based autodiff solver (R/ebalance_autodiff.R))",
  "Maintainer": "Jens Hainmueller <jhain@stanford.edu>",
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    "message": "README: link to project page and explainer\n\nAdds a Documentation section right after Installation pointing to\nthe project landing page (release notes + overview) and the\nself-contained explainer / tutorial on the Stanford site.\n\nCompanion to the cross-link commit on j-hai.github.io that surfaces\nthe GitHub source on the corresponding project page and explainer.\n\nCo-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>\n",
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    "extra/citation.json",
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  "_realowner": "j-hai",
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    "line.searcher",
    "matrixmaker"
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    {
      "page": "balance_table",
      "title": "Per-covariate balance table for an entropy-balancing fit",
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        "balance_table"
      ]
    },
    {
      "page": "baltest.collect",
      "title": "Collect Covariate Balance Statistics",
      "topics": [
        "baltest.collect"
      ]
    },
    {
      "page": "diagnostics",
      "title": "\"Is my fit okay?\" diagnostic check for an entropy-balancing fit",
      "topics": [
        "diagnostics",
        "print.ebalance.diagnostics"
      ]
    },
    {
      "page": "eb",
      "title": "Function for Entropy Balancing",
      "topics": [
        "eb"
      ]
    },
    {
      "page": "ebalance",
      "title": "Entropy balancing",
      "topics": [
        "ebalance"
      ]
    },
    {
      "page": "ebalance-methods",
      "title": "Methods for ebalance and ebalance.trim objects",
      "topics": [
        "plot.ebalance",
        "plot.ebalance.trim",
        "print.ebalance",
        "print.ebalance.trim",
        "print.summary.ebalance",
        "print.summary.ebalance.trim",
        "summary.ebalance",
        "summary.ebalance.trim",
        "weights.ebalance",
        "weights.ebalance.trim"
      ]
    },
    {
      "page": "ebalance.trim",
      "title": "Trimming of Weights for Entropy Balancing",
      "topics": [
        "ebalance.trim"
      ]
    },
    {
      "page": "getsquares",
      "title": "Generate Matrix of Squared Terms",
      "topics": [
        "getsquares"
      ]
    },
    {
      "page": "line.searcher",
      "title": "Optimal step length search for entropy balancing algorithm",
      "topics": [
        "line.searcher"
      ]
    },
    {
      "page": "matrixmaker",
      "title": "Generate Matrix of One-way Interactions and Squared Terms",
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      ]
    }
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        "References"
      ],
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