{
  "_id": "6a23c2f3530b9bc726bdd3fb",
  "Package": "bang",
  "Title": "Bayesian Analysis, No Gibbs",
  "Version": "1.0.4.9000",
  "Date": "2025-02-06",
  "Authors@R": "c(person(c(\"Paul\", \"J.\"), \"Northrop\", email = \"p.northrop@ucl.ac.uk\",\nrole = c(\"aut\", \"cre\", \"cph\")),\nperson(c(\"Benjamin\", \"D.\"), \"Hall\", email = \"benjamin.hall.16@ucl.ac.uk\",\nrole = c(\"aut\", \"cph\")))",
  "Description": "Provides functions for the Bayesian analysis of some\nsimple commonly-used models, without using Markov Chain Monte\nCarlo (MCMC) methods such as Gibbs sampling.  The 'rust'\npackage <https://cran.r-project.org/package=rust> is used to\nsimulate a random sample from the required posterior\ndistribution, using the generalized ratio-of-uniforms method.\nSee Wakefield, Gelfand and Smith (1991)\n<DOI:10.1007/BF01889987> for details. At the moment three\nconjugate hierarchical models are available: beta-binomial,\ngamma-Poisson and a 1-way analysis of variance (ANOVA).",
  "RoxygenNote": "7.3.3",
  "VignetteBuilder": "knitr",
  "URL": "https://paulnorthrop.github.io/bang/,\nhttps://github.com/paulnorthrop/bang",
  "BugReports": "https://github.com/paulnorthrop/bang/issues",
  "License": "GPL (>= 2)",
  "LazyData": "true",
  "Encoding": "UTF-8",
  "Config/testthat/edition": "3",
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://paulnorthrop.r-universe.dev",
  "Date/Publication": "2026-02-06 23:11:09 UTC",
  "RemoteUrl": "https://github.com/paulnorthrop/bang",
  "RemoteRef": "HEAD",
  "RemoteSha": "3ce8d72b600a8ab81ca6248801184e508801c5ec",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-06 06:45:01 UTC",
    "User": "root"
  },
  "Author": "Paul J. Northrop [aut, cre, cph],\nBenjamin D. Hall [aut, cph]",
  "Maintainer": "Paul J. Northrop <p.northrop@ucl.ac.uk>",
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  "_published": "2026-06-06T06:49:23.936Z",
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    "author": "Paul Northrop <p.northrop@ucl.ac.uk>",
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      "role": "Suggests"
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      "role": "Suggests"
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      "package": "testthat",
      "role": "Suggests"
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      "n": 4
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    "bayesian",
    "beta",
    "binomial",
    "gamma",
    "gibbs",
    "hierarchical",
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  "_assets": [
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    "extra/citation.html",
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    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
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  "_realowner": "paulnorthrop",
  "_cranurl": true,
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      "date": "2017-11-20"
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    "pp_check",
    "set_user_prior",
    "sim_pred_beta_binom",
    "sim_pred_gamma_pois",
    "sim_pred_hanova1"
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      "title": "Coagulation time data",
      "object": "coagulation",
      "class": [
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      ],
      "fields": [
        "time",
        "diet"
      ],
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      "table": true,
      "tojson": true
    },
    {
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      "title": "Pump-failure data",
      "object": "pump",
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      ],
      "fields": [
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        "time"
      ],
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      "table": true,
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    },
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      "title": "Rat tumor data",
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      ],
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      "object": "weight_gain",
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      "page": "bang-package",
      "title": "bang: Bayesian Analysis, No Gibbs",
      "topics": [
        "bang-package",
        "bang"
      ]
    },
    {
      "page": "coagulation",
      "title": "Coagulation time data",
      "topics": [
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      ]
    },
    {
      "page": "hanova1",
      "title": "Posterior sampling for a 1-way hierarchical ANOVA",
      "topics": [
        "hanova1"
      ]
    },
    {
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      "title": "Hierarchical Exponential Family Model",
      "topics": [
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      ]
    },
    {
      "page": "plot.hef",
      "title": "Plot diagnostics for a hef object",
      "topics": [
        "plot.hef"
      ]
    },
    {
      "page": "pp_check.hef",
      "title": "Posterior predictive checks for a hef object",
      "topics": [
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        "pp_check.hef"
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    },
    {
      "page": "print.hef",
      "title": "Print method for objects of class \"hef\"",
      "topics": [
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      ]
    },
    {
      "page": "print.summary.hef",
      "title": "Print method for objects of class \"summary.hef\"",
      "topics": [
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    },
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      "title": "Pump-failure data",
      "topics": [
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      "topics": [
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    },
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      "title": "Set a user-defined prior",
      "topics": [
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    },
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      "title": "Simulate from a beta-binomial posterior predictive distribution",
      "topics": [
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    },
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      "title": "Simulate from a gamma-Poisson posterior predictive distribution",
      "topics": [
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      "title": "Simulate from a one-way hierarchical ANOVA posterior predictive distribution",
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      "title": "Summarizing hef objects",
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