{
  "_id": "6a229e01cd65a98ecbd57f93",
  "Package": "holi",
  "Title": "Higher Order Likelihood Inference Web Applications",
  "Version": "0.1.1.9000",
  "Authors@R": "c(\nperson(\"Mackson\", \"Ncube\", , \"macksonncube.stats@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"mightymetrika, LLC\", role = c(\"cph\", \"fnd\"))\n)",
  "Description": "Higher order likelihood inference is a promising approach\nfor analyzing small sample size data. The 'holi' package\nprovides web applications for higher order likelihood\ninference. It currently supports linear, logistic, and Poisson\ngeneralized linear models through the rstar_glm() function,\nbased on Pierce and Bellio (2017) <doi:10.1111/insr.12232> and\n'likelihoodAsy'. The package offers two main features:\nLA_rstar(), which launches an interactive 'shiny' application\nallowing users to fit models with rstar_glm() through their web\nbrowser, and sim_rstar_glm_pgsql(), which streamlines the\nprocess of launching a web-based 'shiny' simulation application\nthat saves results to a user-created 'PostgreSQL' database.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.2",
  "URL": "https://github.com/mightymetrika/holi",
  "BugReports": "https://github.com/mightymetrika/holi/issues",
  "Config/testthat/edition": "3",
  "Config/pak/sysreqs": "cmake make libuv1-dev libpq-dev zlib1g-dev",
  "Repository": "https://mightymetrika.r-universe.dev",
  "Date/Publication": "2024-09-03 15:37:45 UTC",
  "RemoteUrl": "https://github.com/mightymetrika/holi",
  "RemoteRef": "HEAD",
  "RemoteSha": "6599efdaa53a1267bc54d4c3e4c2a787a7768745",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-05 09:56:38 UTC",
    "User": "root"
  },
  "Author": "Mackson Ncube [aut, cre],\nmightymetrika, LLC [cph, fnd]",
  "Maintainer": "Mackson Ncube <macksonncube.stats@gmail.com>",
  "MD5sum": "b656e516e325a24ae71befab251e0c1f",
  "_user": "mightymetrika",
  "_type": "src",
  "_file": "holi_0.1.1.9000.tar.gz",
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  "_created": "2026-06-05T09:56:38.000Z",
  "_published": "2026-06-05T09:59:29.147Z",
  "_distro": "noble",
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  "_buildurl": "https://github.com/r-universe/mightymetrika/actions/runs/27008120893",
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  "_upstream": "https://github.com/mightymetrika/holi",
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    "author": "Mackson Ncube <mightymetrika@proton.me>",
    "committer": "Mackson Ncube <mightymetrika@proton.me>",
    "message": "Increment version number to 0.1.1.9000\n",
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    "email": "macksonncube.stats@gmail.com",
    "login": "mightymetrika",
    "twitter": "@mightymetrika",
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  "_owner": "mightymetrika",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_topics": [
    "data",
    "data-science",
    "statistics"
  ],
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  "_contributors": [
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/holi"
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  "_searchresults": 5,
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  "_assets": [
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  "_homeurl": "https://github.com/mightymetrika/holi",
  "_realowner": "mightymetrika",
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  "_releases": [
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      "date": "2024-07-15"
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      "date": "2024-08-26"
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    "rstar_glm",
    "run_sim_rstar_glm",
    "sim_rstar_glm",
    "sim_rstar_glm_pgsql"
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      "page": "LA_rstar",
      "title": "Launch Shiny App for likelihoodAsy rstar Analysis",
      "topics": [
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      ]
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    {
      "page": "rstar_glm",
      "title": "Compute r* Statistics for Generalized Linear Models",
      "topics": [
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        "rstar_glm.default",
        "rstar_glm.linear",
        "rstar_glm.logistic",
        "rstar_glm.poisson"
      ]
    },
    {
      "page": "run_sim_rstar_glm",
      "title": "Run Multiple Iterations of Simulation and Summarize Results",
      "topics": [
        "run_sim_rstar_glm"
      ]
    },
    {
      "page": "sim_rstar_glm",
      "title": "Simulate Data and Fit GLM and r* Models",
      "topics": [
        "sim_rstar_glm"
      ]
    },
    {
      "page": "sim_rstar_glm_pgsql",
      "title": "Shiny App for Running r* GLM Simulations with PostgreSQL Integration",
      "topics": [
        "sim_rstar_glm_pgsql"
      ]
    }
  ],
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