{
  "_id": "69c111c6b5ac36b5fb6cb6bc",
  "Package": "rstanarm",
  "Type": "Package",
  "Title": "Bayesian Applied Regression Modeling via Stan",
  "Version": "2.32.2",
  "Date": "2025-09-29",
  "Encoding": "UTF-8",
  "Authors@R": "c(person(\"Jonah\", \"Gabry\", email = \"jsg2201@columbia.edu\", role = \"aut\"),\nperson(\"Imad\", \"Ali\", role = \"ctb\"),\nperson(\"Sam\", \"Brilleman\", role = \"ctb\"),\nperson(given = \"Jacqueline Buros\", family = \"Novik\",\nrole = \"ctb\", comment = \"R/stan_jm.R\"),\nperson(\"AstraZeneca\", role = \"ctb\", comment = \"R/stan_jm.R\"),\nperson(\"Trustees of\", \"Columbia University\", role = \"cph\"),\nperson(\"Simon\", \"Wood\", role = \"cph\", comment = \"R/stan_gamm4.R\"),\nperson(\"R Core\", \"Deveopment Team\", role = \"cph\",\ncomment = \"R/stan_aov.R\"),\nperson(\"Douglas\", \"Bates\", role = \"cph\", comment = \"R/pp_data.R\"),\nperson(\"Martin\", \"Maechler\", role = \"cph\", comment = \"R/pp_data.R\"),\nperson(\"Ben\", \"Bolker\", role = \"cph\", comment = \"R/pp_data.R\"),\nperson(\"Steve\", \"Walker\", role = \"cph\", comment = \"R/pp_data.R\"),\nperson(\"Brian\", \"Ripley\", role = \"cph\",\ncomment = \"R/stan_aov.R, R/stan_polr.R\"),\nperson(\"William\", \"Venables\", role = \"cph\", comment = \"R/stan_polr.R\"),\nperson(\"Paul-Christian\", \"Burkner\", email = \"paul.buerkner@gmail.com\",\nrole = \"cph\", comment = \"R/misc.R\"),\nperson(\"Ben\", \"Goodrich\", email = \"benjamin.goodrich@columbia.edu\",\nrole = c(\"cre\", \"aut\")))",
  "Description": "Estimates previously compiled regression models using the\n'rstan' package, which provides the R interface to the Stan C++\nlibrary for Bayesian estimation. Users specify models via the\ncustomary R syntax with a formula and data.frame plus some\nadditional arguments for priors.",
  "License": "GPL (>=3)",
  "SystemRequirements": "GNU make, pandoc (>= 1.12.3), pandoc-citeproc",
  "VignetteBuilder": "knitr",
  "LazyData": "true",
  "UseLTO": "true",
  "NeedsCompilation": "yes",
  "URL": "https://mc-stan.org/rstanarm/, https://discourse.mc-stan.org",
  "BugReports": "https://github.com/stan-dev/rstanarm/issues",
  "RoxygenNote": "7.3.3",
  "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libxml2-dev\nzlib1g-dev",
  "Repository": "https://r-multiverse.r-universe.dev",
  "Date/Publication": "2025-10-06 21:04:15 UTC",
  "RemoteUrl": "https://github.com/stan-dev/rstanarm",
  "RemoteRef": "v2.32.2",
  "RemoteSha": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
  "Packaged": {
    "Date": "2026-03-23 09:25:47 UTC",
    "User": "root"
  },
  "Author": "Jonah Gabry [aut],\nImad Ali [ctb],\nSam Brilleman [ctb],\nJacqueline Buros Novik [ctb] (R/stan_jm.R),\nAstraZeneca [ctb] (R/stan_jm.R),\nTrustees of Columbia University [cph],\nSimon Wood [cph] (R/stan_gamm4.R),\nR Core Deveopment Team [cph] (R/stan_aov.R),\nDouglas Bates [cph] (R/pp_data.R),\nMartin Maechler [cph] (R/pp_data.R),\nBen Bolker [cph] (R/pp_data.R),\nSteve Walker [cph] (R/pp_data.R),\nBrian Ripley [cph] (R/stan_aov.R, R/stan_polr.R),\nWilliam Venables [cph] (R/stan_polr.R),\nPaul-Christian Burkner [cph] (R/misc.R),\nBen Goodrich [cre, aut]",
  "Maintainer": "Ben Goodrich <benjamin.goodrich@columbia.edu>",
  "MD5sum": "2e21244930f6bf1f98dcab3e7c7ab85f",
  "_user": "r-multiverse",
  "_type": "src",
  "_file": "rstanarm_2.32.2.tar.gz",
  "_fileid": "b94916967d758979861bb93a754e7224e40aba0557206d0d8ddd0a4a1e4aad85",
  "_filesize": 2360952,
  "_sha256": "b94916967d758979861bb93a754e7224e40aba0557206d0d8ddd0a4a1e4aad85",
  "_created": "2026-03-23T09:25:47.000Z",
  "_published": "2026-03-23T10:11:18.033Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 68156083728,
      "time": 997,
      "config": "linux-devel-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6055968519"
    },
    {
      "job": 68156083706,
      "time": 962,
      "config": "linux-devel-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6055959428"
    },
    {
      "job": 68156083677,
      "time": 1028,
      "config": "linux-release-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "6055976811"
    },
    {
      "job": 68156083652,
      "time": 956,
      "config": "linux-release-x86_64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "6055957776"
    },
    {
      "job": 68156083672,
      "time": 894,
      "config": "macos-devel-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6055996844"
    },
    {
      "job": 68156083657,
      "time": 1943,
      "config": "macos-devel-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6056251120"
    },
    {
      "job": 68156083668,
      "time": 902,
      "config": "macos-release-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "6055994432"
    },
    {
      "job": 68156083711,
      "time": 1411,
      "config": "macos-release-x86_64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "6056114176"
    },
    {
      "job": 68152497775,
      "time": 1595,
      "config": "source",
      "r": "4.5.2",
      "check": "OK",
      "artifact": "6055699642"
    },
    {
      "job": 68156083622,
      "time": 185,
      "config": "wasm-release",
      "r": "4.5.1",
      "check": "FAIL",
      "artifact": ""
    },
    {
      "job": 68156083627,
      "time": 1554,
      "config": "windows-devel",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "6056123192"
    },
    {
      "job": 68156083688,
      "time": 1222,
      "config": "windows-release",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "6056031104"
    }
  ],
  "_buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/stan-dev/rstanarm",
  "_commit": {
    "id": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
    "author": "Ben Goodrich <goodrich.ben@gmail.com>",
    "committer": "Ben Goodrich <goodrich.ben@gmail.com>",
    "message": "drop problematic URL\n",
    "time": 1759784655
  },
  "_maintainer": {
    "name": "Ben Goodrich",
    "email": "benjamin.goodrich@columbia.edu",
    "login": "bgoodri",
    "uuid": 3386282
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.4.0",
      "role": "Depends"
    },
    {
      "package": "Rcpp",
      "version": ">= 0.12.0",
      "role": "Depends"
    },
    {
      "package": "methods",
      "role": "Depends"
    },
    {
      "package": "StanHeaders",
      "version": ">= 2.32.0",
      "role": "LinkingTo"
    },
    {
      "package": "rstan",
      "version": ">= 2.32.0",
      "role": "LinkingTo"
    },
    {
      "package": "BH",
      "version": ">= 1.72.0-2",
      "role": "LinkingTo"
    },
    {
      "package": "Rcpp",
      "version": ">= 0.12.0",
      "role": "LinkingTo"
    },
    {
      "package": "RcppEigen",
      "version": ">= 0.3.3.3.0",
      "role": "LinkingTo"
    },
    {
      "package": "RcppParallel",
      "version": ">= 5.0.1",
      "role": "LinkingTo"
    },
    {
      "package": "bayesplot",
      "version": ">= 1.7.0",
      "role": "Imports"
    },
    {
      "package": "ggplot2",
      "version": ">= 2.2.1",
      "role": "Imports"
    },
    {
      "package": "lme4",
      "version": ">= 1.1-8",
      "role": "Imports"
    },
    {
      "package": "loo",
      "version": ">= 2.1.0",
      "role": "Imports"
    },
    {
      "package": "Matrix",
      "version": ">= 1.2-13",
      "role": "Imports"
    },
    {
      "package": "nlme",
      "version": ">= 3.1-124",
      "role": "Imports"
    },
    {
      "package": "posterior",
      "role": "Imports"
    },
    {
      "package": "rstan",
      "version": ">= 2.32.0",
      "role": "Imports"
    },
    {
      "package": "rstantools",
      "version": ">= 2.1.0",
      "role": "Imports"
    },
    {
      "package": "shinystan",
      "version": ">= 2.3.0",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "survival",
      "version": ">= 2.40.1",
      "role": "Imports"
    },
    {
      "package": "RcppParallel",
      "version": ">= 5.0.1",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "reformulas",
      "role": "Imports"
    },
    {
      "package": "biglm",
      "role": "Suggests"
    },
    {
      "package": "betareg",
      "role": "Suggests"
    },
    {
      "package": "data.table",
      "version": ">= 1.10.0",
      "role": "Suggests"
    },
    {
      "package": "digest",
      "role": "Suggests"
    },
    {
      "package": "gridExtra",
      "role": "Suggests"
    },
    {
      "package": "HSAUR3",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "version": ">= 1.15.1",
      "role": "Suggests"
    },
    {
      "package": "MASS",
      "role": "Suggests"
    },
    {
      "package": "mgcv",
      "version": ">= 1.8-13",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "roxygen2",
      "role": "Suggests"
    },
    {
      "package": "StanHeaders",
      "version": ">= 2.21.0",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "version": ">= 1.0.2",
      "role": "Suggests"
    },
    {
      "package": "gamm4",
      "role": "Suggests"
    },
    {
      "package": "shiny",
      "role": "Suggests"
    },
    {
      "package": "V8",
      "role": "Suggests"
    }
  ],
  "_owner": "stan-dev",
  "_selfowned": false,
  "_usedby": 14,
  "_updates": [
    {
      "week": "2025-21",
      "n": 1
    },
    {
      "week": "2025-22",
      "n": 2
    },
    {
      "week": "2025-39",
      "n": 2
    },
    {
      "week": "2025-40",
      "n": 2
    },
    {
      "week": "2025-41",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "v2.32.2",
      "date": "2025-10-06"
    }
  ],
  "_topics": [
    "bayesian",
    "bayesian-data-analysis",
    "bayesian-inference",
    "bayesian-methods",
    "bayesian-statistics",
    "multilevel-models",
    "rstan",
    "rstanarm",
    "stan",
    "statistical-modeling",
    "cpp"
  ],
  "_stars": 399,
  "_contributors": [
    {
      "user": "jgabry",
      "count": 1598,
      "uuid": 7796803
    },
    {
      "user": "bgoodri",
      "count": 1190,
      "uuid": 3386282
    },
    {
      "user": "sambrilleman",
      "count": 293,
      "uuid": 19546444
    },
    {
      "user": "imadmali",
      "count": 103,
      "uuid": 16767381
    },
    {
      "user": "avehtari",
      "count": 46,
      "uuid": 6705400
    },
    {
      "user": "andrjohns",
      "count": 31,
      "uuid": 27717896
    },
    {
      "user": "visruthsk",
      "count": 11,
      "uuid": 67435125
    },
    {
      "user": "pamelanluna",
      "count": 8,
      "uuid": 8870923
    },
    {
      "user": "yoshidk6",
      "count": 5,
      "uuid": 2650321
    },
    {
      "user": "mcol",
      "count": 5,
      "uuid": 6078177
    },
    {
      "user": "yihui",
      "count": 5,
      "uuid": 163582
    },
    {
      "user": "lauken13",
      "count": 4,
      "uuid": 3905048
    },
    {
      "user": "wlandau",
      "count": 3,
      "uuid": 1580860
    },
    {
      "user": "statwonk",
      "count": 3,
      "uuid": 1160090
    },
    {
      "user": "danschrage",
      "count": 3,
      "uuid": 14733529
    },
    {
      "user": "jburos",
      "count": 3,
      "uuid": 923453
    },
    {
      "user": "storopoli",
      "count": 2,
      "uuid": 43353831
    },
    {
      "user": "malcolmbarrett",
      "count": 2,
      "uuid": 23123711
    },
    {
      "user": "bbolker",
      "count": 1,
      "uuid": 78918
    },
    {
      "user": "strengejacke",
      "count": 1,
      "uuid": 26301769
    },
    {
      "user": "syclik",
      "count": 1,
      "uuid": 425751
    },
    {
      "user": "hpcurtis",
      "count": 1,
      "uuid": 136170998
    },
    {
      "user": "unrealmcg",
      "count": 1,
      "uuid": 33672174
    },
    {
      "user": "paasim",
      "count": 1,
      "uuid": 8017733
    },
    {
      "user": "michaelchirico",
      "count": 1,
      "uuid": 7606389
    },
    {
      "user": "tjmahr",
      "count": 1,
      "uuid": 1890315
    },
    {
      "user": "fartist",
      "count": 1,
      "uuid": 14242695
    },
    {
      "user": "singmann",
      "count": 1,
      "uuid": 1902102
    }
  ],
  "_userbio": {
    "uuid": 161461790,
    "type": "organization",
    "name": "R-multiverse",
    "description": "A community-curated collection of R package releases, powered by R-universe"
  },
  "_downloads": {
    "count": 17761,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/rstanarm"
  },
  "_mentions": 70,
  "_devurl": "https://github.com/stan-dev/rstanarm",
  "_pkgdown": "https://mc-stan.org/rstanarm/",
  "_searchresults": 6752,
  "_rbuild": "4.5.2",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "extra/rstanarm.html",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/stan-dev/rstanarm",
  "_realowner": "stan-dev",
  "_cranurl": true,
  "_releases": [
    {
      "version": "2.9.0-1",
      "date": "2016-01-09"
    },
    {
      "version": "2.9.0-3",
      "date": "2016-02-13"
    },
    {
      "version": "2.9.0-4",
      "date": "2016-05-24"
    },
    {
      "version": "2.10.1",
      "date": "2016-06-25"
    },
    {
      "version": "2.11.1",
      "date": "2016-07-29"
    },
    {
      "version": "2.12.1",
      "date": "2016-09-13"
    },
    {
      "version": "2.13.1",
      "date": "2016-11-20"
    },
    {
      "version": "2.14.1",
      "date": "2017-01-17"
    },
    {
      "version": "2.15.2",
      "date": "2017-04-19"
    },
    {
      "version": "2.15.3",
      "date": "2017-04-29"
    },
    {
      "version": "2.17.2",
      "date": "2017-12-21"
    },
    {
      "version": "2.17.3",
      "date": "2018-02-18"
    },
    {
      "version": "2.17.4",
      "date": "2018-04-13"
    },
    {
      "version": "2.18.1",
      "date": "2018-10-21"
    },
    {
      "version": "2.18.2",
      "date": "2018-11-10"
    },
    {
      "version": "2.19.2",
      "date": "2019-10-03"
    },
    {
      "version": "2.19.3",
      "date": "2020-02-11"
    },
    {
      "version": "2.21.1",
      "date": "2020-07-20"
    },
    {
      "version": "2.21.3",
      "date": "2022-04-09"
    },
    {
      "version": "2.21.4",
      "date": "2023-04-08"
    },
    {
      "version": "2.26.1",
      "date": "2023-09-13"
    },
    {
      "version": "2.32.1",
      "date": "2024-01-18"
    },
    {
      "version": "2.32.2",
      "date": "2025-10-03"
    }
  ],
  "_exports": [
    "as_draws",
    "as_draws_array",
    "as_draws_df",
    "as_draws_list",
    "as_draws_matrix",
    "as_draws_rvars",
    "bayes_R2",
    "cauchy",
    "compare_models",
    "decov",
    "default_prior_coef",
    "default_prior_intercept",
    "dirichlet",
    "exponential",
    "fixef",
    "get_x",
    "get_y",
    "get_z",
    "hs",
    "hs_plus",
    "invlogit",
    "kfold",
    "laplace",
    "lasso",
    "launch_shinystan",
    "lkj",
    "log_lik",
    "logit",
    "loo",
    "loo_compare",
    "loo_linpred",
    "loo_model_weights",
    "loo_predict",
    "loo_predictive_interval",
    "loo_R2",
    "neg_binomial_2",
    "ngrps",
    "normal",
    "nsamples",
    "pairs_condition",
    "pairs_style_np",
    "plot_nonlinear",
    "plot_stack_jm",
    "posterior_epred",
    "posterior_interval",
    "posterior_linpred",
    "posterior_predict",
    "posterior_survfit",
    "posterior_traj",
    "posterior_vs_prior",
    "pp_check",
    "pp_validate",
    "predictive_error",
    "predictive_interval",
    "prior_options",
    "prior_summary",
    "product_normal",
    "ps_check",
    "R2",
    "ranef",
    "se",
    "sigma",
    "stan_aov",
    "stan_betareg",
    "stan_betareg.fit",
    "stan_biglm",
    "stan_biglm.fit",
    "stan_clogit",
    "stan_gamm4",
    "stan_glm",
    "stan_glm.fit",
    "stan_glm.nb",
    "stan_glmer",
    "stan_glmer.nb",
    "stan_jm",
    "stan_lm",
    "stan_lm.fit",
    "stan_lm.wfit",
    "stan_lmer",
    "stan_mvmer",
    "stan_nlmer",
    "stan_polr",
    "stan_polr.fit",
    "stanjm_list",
    "stanmvreg_list",
    "stanreg_list",
    "student_t",
    "Surv",
    "VarCorr",
    "waic"
  ],
  "_datasets": [
    {
      "name": "bball1970",
      "title": "Datasets for rstanarm examples",
      "object": "bball1970",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Player",
        "AB",
        "Hits",
        "RemainingAB",
        "RemainingHits"
      ],
      "rows": 18,
      "table": true,
      "tojson": true
    },
    {
      "name": "bball2006",
      "title": "Datasets for rstanarm examples",
      "object": "bball2006",
      "class": [
        "data.frame"
      ],
      "fields": [
        "y",
        "K"
      ],
      "rows": 308,
      "table": true,
      "tojson": true
    },
    {
      "name": "kidiq",
      "title": "Datasets for rstanarm examples",
      "object": "kidiq",
      "class": [
        "data.frame"
      ],
      "fields": [
        "kid_score",
        "mom_hs",
        "mom_iq",
        "mom_age"
      ],
      "rows": 434,
      "table": true,
      "tojson": true
    },
    {
      "name": "mortality",
      "title": "Datasets for rstanarm examples",
      "object": "mortality",
      "class": [
        "data.frame"
      ],
      "fields": [
        "y",
        "K"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "pbcLong",
      "title": "Datasets for rstanarm examples",
      "object": "pbcLong",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "age",
        "sex",
        "trt",
        "year",
        "logBili",
        "albumin",
        "platelet"
      ],
      "rows": 304,
      "table": true,
      "tojson": true
    },
    {
      "name": "pbcSurv",
      "title": "Datasets for rstanarm examples",
      "object": "pbcSurv",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "age",
        "sex",
        "trt",
        "futimeYears",
        "status",
        "death"
      ],
      "rows": 40,
      "table": true,
      "tojson": true
    },
    {
      "name": "radon",
      "title": "Datasets for rstanarm examples",
      "object": "radon",
      "class": [
        "data.frame"
      ],
      "fields": [
        "floor",
        "county",
        "log_radon",
        "log_uranium"
      ],
      "rows": 919,
      "table": true,
      "tojson": true
    },
    {
      "name": "roaches",
      "title": "Datasets for rstanarm examples",
      "object": "roaches",
      "class": [
        "data.frame"
      ],
      "fields": [
        "y",
        "roach1",
        "treatment",
        "senior",
        "exposure2"
      ],
      "rows": 262,
      "table": true,
      "tojson": true
    },
    {
      "name": "tumors",
      "title": "Datasets for rstanarm examples",
      "object": "tumors",
      "class": [
        "data.frame"
      ],
      "fields": [
        "y",
        "K"
      ],
      "rows": 71,
      "table": true,
      "tojson": true
    },
    {
      "name": "wells",
      "title": "Datasets for rstanarm examples",
      "object": "wells",
      "class": [
        "data.frame"
      ],
      "fields": [
        "switch",
        "arsenic",
        "dist",
        "assoc",
        "educ"
      ],
      "rows": 3020,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "rstanarm-package",
      "title": "Applied Regression Modeling via RStan",
      "topics": [
        "rstanarm-package",
        "rstanarm"
      ]
    },
    {
      "page": "adapt_delta",
      "title": "'adapt_delta': Target average acceptance probability",
      "topics": [
        "adapt_delta"
      ]
    },
    {
      "page": "as.matrix.stanreg",
      "title": "Extract the posterior sample",
      "topics": [
        "as.array.stanreg",
        "as.data.frame.stanreg",
        "as.matrix.stanreg"
      ]
    },
    {
      "page": "available-algorithms",
      "title": "Estimation algorithms available for 'rstanarm' models",
      "topics": [
        "available-algorithms"
      ]
    },
    {
      "page": "available-models",
      "title": "Modeling functions available in 'rstanarm'",
      "topics": [
        "available-models"
      ]
    },
    {
      "page": "bayes_R2.stanreg",
      "title": "Compute a Bayesian version of R-squared or LOO-adjusted R-squared for regression models.",
      "topics": [
        "bayes_R2",
        "bayes_R2.stanreg",
        "loo_R2",
        "loo_R2.stanreg"
      ]
    },
    {
      "page": "example_jm",
      "title": "Example joint longitudinal and time-to-event model",
      "topics": [
        "example_jm"
      ]
    },
    {
      "page": "example_model",
      "title": "Example model",
      "topics": [
        "example_model"
      ]
    },
    {
      "page": "kfold.stanreg",
      "title": "K-fold cross-validation",
      "topics": [
        "kfold",
        "kfold.stanreg"
      ]
    },
    {
      "page": "launch_shinystan.stanreg",
      "title": "Using the ShinyStan GUI with rstanarm models",
      "topics": [
        "launch_shinystan",
        "launch_shinystan.stanreg"
      ]
    },
    {
      "page": "log_lik.stanreg",
      "title": "Pointwise log-likelihood matrix",
      "topics": [
        "log_lik",
        "log_lik.stanjm",
        "log_lik.stanmvreg",
        "log_lik.stanreg"
      ]
    },
    {
      "page": "logit",
      "title": "Logit and inverse logit",
      "topics": [
        "invlogit",
        "logit"
      ]
    },
    {
      "page": "loo_predict.stanreg",
      "title": "Compute weighted expectations using LOO",
      "topics": [
        "loo_linpred",
        "loo_linpred.stanreg",
        "loo_predict",
        "loo_predict.stanreg",
        "loo_predictive_interval",
        "loo_predictive_interval.stanreg"
      ]
    },
    {
      "page": "loo.stanreg",
      "title": "Information criteria and cross-validation",
      "topics": [
        "compare_models",
        "loo",
        "loo.stanreg",
        "loo_compare",
        "loo_compare.stanreg",
        "loo_compare.stanreg_list",
        "loo_model_weights",
        "loo_model_weights.stanreg_list",
        "waic",
        "waic.stanreg"
      ]
    },
    {
      "page": "neg_binomial_2",
      "title": "Family function for negative binomial GLMs",
      "topics": [
        "neg_binomial_2"
      ]
    },
    {
      "page": "stanreg-methods",
      "title": "Methods for stanreg objects",
      "topics": [
        "coef.stanreg",
        "confint.stanreg",
        "fitted.stanreg",
        "fixef",
        "fixef.stanreg",
        "ngrps",
        "ngrps.stanreg",
        "nobs.stanmvreg",
        "nobs.stanreg",
        "nsamples",
        "nsamples.stanreg",
        "ranef",
        "ranef.stanreg",
        "residuals.stanreg",
        "se.stanreg",
        "sigma",
        "sigma.stanreg",
        "stanreg-methods",
        "update.stanreg",
        "VarCorr",
        "VarCorr.stanreg",
        "vcov.stanreg"
      ]
    },
    {
      "page": "pairs.stanreg",
      "title": "Pairs method for stanreg objects",
      "topics": [
        "pairs.stanreg",
        "pairs_condition",
        "pairs_style_np"
      ]
    },
    {
      "page": "plot.predict.stanjm",
      "title": "Plot the estimated subject-specific or marginal longitudinal trajectory",
      "topics": [
        "plot.predict.stanjm"
      ]
    },
    {
      "page": "plot.stanreg",
      "title": "Plot method for stanreg objects",
      "topics": [
        "plot.stanreg"
      ]
    },
    {
      "page": "plot.survfit.stanjm",
      "title": "Plot the estimated subject-specific or marginal survival function",
      "topics": [
        "plot.survfit.stanjm",
        "plot_stack_jm"
      ]
    },
    {
      "page": "posterior_interval.stanreg",
      "title": "Posterior uncertainty intervals",
      "topics": [
        "posterior_interval",
        "posterior_interval.stanreg"
      ]
    },
    {
      "page": "posterior_linpred.stanreg",
      "title": "Posterior distribution of the (possibly transformed) linear predictor",
      "topics": [
        "posterior_epred",
        "posterior_epred.stanreg",
        "posterior_linpred",
        "posterior_linpred.stanreg"
      ]
    },
    {
      "page": "posterior_predict.stanreg",
      "title": "Draw from posterior predictive distribution",
      "topics": [
        "posterior_predict",
        "posterior_predict.stanmvreg",
        "posterior_predict.stanreg"
      ]
    },
    {
      "page": "posterior_survfit",
      "title": "Estimate subject-specific or standardised survival probabilities",
      "topics": [
        "posterior_survfit"
      ]
    },
    {
      "page": "posterior_traj",
      "title": "Estimate the subject-specific or marginal longitudinal trajectory",
      "topics": [
        "posterior_traj"
      ]
    },
    {
      "page": "posterior_vs_prior",
      "title": "Juxtapose prior and posterior",
      "topics": [
        "posterior_vs_prior",
        "posterior_vs_prior.stanreg"
      ]
    },
    {
      "page": "pp_check.stanreg",
      "title": "Graphical posterior predictive checks",
      "topics": [
        "pp_check",
        "pp_check.stanreg"
      ]
    },
    {
      "page": "pp_validate",
      "title": "Model validation via simulation",
      "topics": [
        "pp_validate"
      ]
    },
    {
      "page": "predict.stanreg",
      "title": "Predict method for stanreg objects",
      "topics": [
        "predict.stanreg"
      ]
    },
    {
      "page": "predictive_error.stanreg",
      "title": "In-sample or out-of-sample predictive errors",
      "topics": [
        "predictive_error",
        "predictive_error.matrix",
        "predictive_error.ppd",
        "predictive_error.stanreg"
      ]
    },
    {
      "page": "predictive_interval.stanreg",
      "title": "Predictive intervals",
      "topics": [
        "predictive_interval",
        "predictive_interval.matrix",
        "predictive_interval.ppd",
        "predictive_interval.stanreg"
      ]
    },
    {
      "page": "print.stanreg",
      "title": "Print method for stanreg objects",
      "topics": [
        "print.stanmvreg",
        "print.stanreg"
      ]
    },
    {
      "page": "prior_summary.stanreg",
      "title": "Summarize the priors used for an rstanarm model",
      "topics": [
        "prior_summary",
        "prior_summary.stanreg"
      ]
    },
    {
      "page": "priors",
      "title": "Prior distributions and options",
      "topics": [
        "cauchy",
        "decov",
        "default_prior_coef",
        "default_prior_intercept",
        "dirichlet",
        "exponential",
        "hs",
        "hs_plus",
        "laplace",
        "lasso",
        "lkj",
        "normal",
        "priors",
        "product_normal",
        "R2",
        "student_t"
      ]
    },
    {
      "page": "ps_check",
      "title": "Graphical checks of the estimated survival function",
      "topics": [
        "ps_check"
      ]
    },
    {
      "page": "QR-argument",
      "title": "The 'QR' argument",
      "topics": [
        "QR-argument"
      ]
    },
    {
      "page": "rstanarm-datasets",
      "title": "Datasets for rstanarm examples",
      "topics": [
        "bball1970",
        "bball2006",
        "kidiq",
        "mortality",
        "pbcLong",
        "pbcSurv",
        "radon",
        "roaches",
        "rstanarm-datasets",
        "tumors",
        "wells"
      ]
    },
    {
      "page": "rstanarm-deprecated",
      "title": "Deprecated functions",
      "topics": [
        "prior_options",
        "rstanarm-deprecated"
      ]
    },
    {
      "page": "stan_lm",
      "title": "Bayesian regularized linear models via Stan",
      "topics": [
        "stan_aov",
        "stan_lm",
        "stan_lm.fit",
        "stan_lm.wfit"
      ]
    },
    {
      "page": "stan_betareg",
      "title": "Bayesian beta regression models via Stan",
      "topics": [
        "stan_betareg",
        "stan_betareg.fit"
      ]
    },
    {
      "page": "stan_biglm",
      "title": "Bayesian regularized linear but big models via Stan",
      "topics": [
        "stan_biglm",
        "stan_biglm.fit"
      ]
    },
    {
      "page": "stan_clogit",
      "title": "Conditional logistic (clogit) regression models via Stan",
      "topics": [
        "stan_clogit"
      ]
    },
    {
      "page": "stan_gamm4",
      "title": "Bayesian generalized linear additive models with optional group-specific terms via Stan",
      "topics": [
        "plot_nonlinear",
        "stan_gamm4"
      ]
    },
    {
      "page": "stan_glm",
      "title": "Bayesian generalized linear models via Stan",
      "topics": [
        "stan_glm",
        "stan_glm.fit",
        "stan_glm.nb"
      ]
    },
    {
      "page": "stan_glmer",
      "title": "Bayesian generalized linear models with group-specific terms via Stan",
      "topics": [
        "stan_glmer",
        "stan_glmer.nb",
        "stan_lmer"
      ]
    },
    {
      "page": "stan_jm",
      "title": "Bayesian joint longitudinal and time-to-event models via Stan",
      "topics": [
        "stan_jm"
      ]
    },
    {
      "page": "stan_mvmer",
      "title": "Bayesian multivariate generalized linear models with correlated group-specific terms via Stan",
      "topics": [
        "stan_mvmer"
      ]
    },
    {
      "page": "stan_nlmer",
      "title": "Bayesian nonlinear models with group-specific terms via Stan",
      "topics": [
        "stan_nlmer"
      ]
    },
    {
      "page": "stan_polr",
      "title": "Bayesian ordinal regression models via Stan",
      "topics": [
        "stan_polr",
        "stan_polr.fit"
      ]
    },
    {
      "page": "stanmvreg-methods",
      "title": "Methods for stanmvreg objects",
      "topics": [
        "coef.stanmvreg",
        "fitted.stanmvreg",
        "fixef.stanmvreg",
        "formula.stanmvreg",
        "ngrps.stanmvreg",
        "ranef.stanmvreg",
        "residuals.stanmvreg",
        "se.stanmvreg",
        "sigma.stanmvreg",
        "stanmvreg-methods",
        "update.stanjm",
        "update.stanmvreg"
      ]
    },
    {
      "page": "stanreg_list",
      "title": "Create lists of fitted model objects, combine them, or append new models to existing lists of models.",
      "topics": [
        "print.stanreg_list",
        "stanjm_list",
        "stanmvreg_list",
        "stanreg_list"
      ]
    },
    {
      "page": "stanreg-draws-formats",
      "title": "Create a 'draws' object from a 'stanreg' object",
      "topics": [
        "as_draws",
        "as_draws.stanreg",
        "as_draws_array",
        "as_draws_array.stanreg",
        "as_draws_df",
        "as_draws_df.stanreg",
        "as_draws_list",
        "as_draws_list.stanreg",
        "as_draws_matrix",
        "as_draws_matrix.stanreg",
        "as_draws_rvars",
        "as_draws_rvars.stanreg",
        "stanreg-draws-formats"
      ]
    },
    {
      "page": "stanreg-objects",
      "title": "Fitted model objects",
      "topics": [
        "stanreg-objects"
      ]
    },
    {
      "page": "summary.stanreg",
      "title": "Summary method for stanreg objects",
      "topics": [
        "as.data.frame.summary.stanreg",
        "print.summary.stanmvreg",
        "print.summary.stanreg",
        "summary.stanmvreg",
        "summary.stanreg"
      ]
    }
  ],
  "_pkglogo": "https://github.com/stan-dev/rstanarm/raw/v2.32.2/man/figures/logo.svg",
  "_readme": "https://github.com/stan-dev/rstanarm/raw/v2.32.2/README.md",
  "_rundeps": [
    "abind",
    "backports",
    "base64enc",
    "bayesplot",
    "BH",
    "boot",
    "bslib",
    "cachem",
    "callr",
    "checkmate",
    "cli",
    "colourpicker",
    "commonmark",
    "cpp11",
    "crosstalk",
    "desc",
    "digest",
    "distributional",
    "dplyr",
    "DT",
    "dygraphs",
    "evaluate",
    "farver",
    "fastmap",
    "fontawesome",
    "fs",
    "generics",
    "ggplot2",
    "ggridges",
    "glue",
    "gridExtra",
    "gtable",
    "gtools",
    "highr",
    "htmltools",
    "htmlwidgets",
    "httpuv",
    "igraph",
    "inline",
    "isoband",
    "jquerylib",
    "jsonlite",
    "knitr",
    "labeling",
    "later",
    "lattice",
    "lazyeval",
    "lifecycle",
    "litedown",
    "lme4",
    "loo",
    "magrittr",
    "markdown",
    "MASS",
    "Matrix",
    "matrixStats",
    "memoise",
    "mime",
    "miniUI",
    "minqa",
    "nlme",
    "nloptr",
    "numDeriv",
    "otel",
    "pillar",
    "pkgbuild",
    "pkgconfig",
    "plyr",
    "posterior",
    "processx",
    "promises",
    "ps",
    "purrr",
    "QuickJSR",
    "R6",
    "rappdirs",
    "rbibutils",
    "RColorBrewer",
    "Rcpp",
    "RcppEigen",
    "RcppParallel",
    "Rdpack",
    "reformulas",
    "reshape2",
    "rlang",
    "rmarkdown",
    "rstan",
    "rstantools",
    "S7",
    "sass",
    "scales",
    "shiny",
    "shinyjs",
    "shinystan",
    "shinythemes",
    "sourcetools",
    "StanHeaders",
    "stringi",
    "stringr",
    "survival",
    "tensorA",
    "threejs",
    "tibble",
    "tidyr",
    "tidyselect",
    "tinytex",
    "utf8",
    "vctrs",
    "viridisLite",
    "withr",
    "xfun",
    "xtable",
    "xts",
    "yaml",
    "zoo"
  ],
  "_sysdeps": [
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    }
  ],
  "_vignettes": [
    {
      "source": "pooling.Rmd",
      "filename": "pooling.html",
      "title": "Hierarchical Partial Pooling for Repeated Binary Trials",
      "author": "Bob Carpenter, Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Repeated Binary Trials",
        "Baseball Hits (Efron and Morris 1975)",
        "Pooling",
        "Fitting the Models",
        "Complete Pooling",
        "No Pooling",
        "Partial Pooling",
        "Observed vs. Estimated Chance of Success",
        "Posterior Predictive Distribution",
        "Evaluating Held-Out Data Predictions",
        "Simulating Replicated Data",
        "Prediction for New Trials",
        "Calibration",
        "Sharpness",
        "Why Evaluate with the Predictive Posterior?",
        "$\\log E[p(\\tilde{y} , | , \\theta)]$ vs $E[\\log p(\\tilde{y} , | , \\theta)]$",
        "Posterior expectation of the log predictive density",
        "Approximating the expected log predictive density",
        "Predicting New Observations",
        "Estimating Event Probabilities",
        "Multiple Comparisons",
        "Ranking",
        "Who has the Highest Chance of Success?",
        "Graphical Posterior Predictive Checks",
        "Test Statistics and Bayesian $p$-Values",
        "Comparing Observed and Replicated Data",
        "Discussion",
        "Exercises",
        "References",
        "Additional Data Sets",
        "Rat tumors (N = 71)",
        "Surgical mortality (N = 12)",
        "Baseball hits 1996 AL (N = 308)"
      ],
      "created": "2016-02-09 04:28:31",
      "modified": "2025-09-29 14:51:55",
      "commits": 27
    },
    {
      "source": "rstanarm.Rmd",
      "filename": "rstanarm.html",
      "title": "How to Use the rstanarm Package",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Step 1: Specify a posterior distribution",
        "Note on \"prior beliefs\" and default priors",
        "Step 2: Draw from the posterior distribution",
        "Step 3: Criticize the model",
        "Step 4: Analyze manipulations of predictors",
        "Troubleshooting",
        "Markov chains did not converge",
        "Divergent transitions",
        "Maximum treedepth exceeded",
        "Conclusion",
        "References"
      ],
      "created": "2015-08-29 23:30:36",
      "modified": "2025-09-29 14:51:55",
      "commits": 51
    },
    {
      "source": "mrp.Rmd",
      "filename": "mrp.html",
      "title": "MRP with rstanarm",
      "author": "Lauren Kennedy and Jonah Gabry",
      "engine": "knitr::rmarkdown",
      "headings": [
        "The Data",
        "Exploring Graphically",
        "Comparing sample to population",
        "Effect of the post-stratification variable on preference for cats",
        "Interaction effect",
        "Design effect",
        "MRP with rstanarm",
        "Population Estimate",
        "Estimates for states",
        "Other formats",
        "Alternate methods of modelling",
        "Appendix",
        "Examples of other formulas",
        "Code to simulate the data",
        "References"
      ],
      "created": "2019-09-16 18:17:56",
      "modified": "2020-01-15 00:52:05",
      "commits": 12
    },
    {
      "source": "priors.Rmd",
      "filename": "priors.html",
      "title": "Prior Distributions for rstanarm Models",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "July 2020 Update",
        "Introduction",
        "Default (Weakly Informative) Prior Distributions",
        "Default priors and scale adjustments",
        "Regression coefficients",
        "Intercept",
        "Auxiliary parameters",
        "Note on data-based priors",
        "Disabling prior scale adjustments",
        "How to Specify Flat Priors (and why you typically shouldn't)",
        "Uninformative is usually unwarranted and unrealistic (flat is frequently frivolous and fictional)",
        "Specifying flat priors",
        "Informative Prior Distributions"
      ],
      "created": "2017-04-11 08:39:45",
      "modified": "2022-03-16 19:55:10",
      "commits": 15
    },
    {
      "source": "ab-testing.Rmd",
      "filename": "ab-testing.html",
      "title": "Probabilistic A/B Testing with rstanarm",
      "author": "Imad Ali",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Abstract",
        "Introduction",
        "Continuous Data",
        "Count Data",
        "Benefits of Bayesian Methods",
        "Conclusion",
        "Acknowlegements",
        "References",
        "Appendix A: Refresher on p-values",
        "Appendix B: Hierarchical Example"
      ],
      "created": "2020-10-15 23:27:44",
      "modified": "2025-10-06 21:04:15",
      "commits": 4
    },
    {
      "source": "aov.Rmd",
      "filename": "aov.html",
      "title": "Estimating ANOVA Models with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "Priors",
        "Example",
        "Conclusion"
      ],
      "created": "2015-08-31 00:18:16",
      "modified": "2020-01-15 00:52:05",
      "commits": 24
    },
    {
      "source": "betareg.Rmd",
      "filename": "betareg.html",
      "title": "Modeling Rates/Proportions using Beta Regression with rstanarm",
      "author": "Imad Ali, Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "Priors",
        "Posterior",
        "An Example Using Simulated Data",
        "An Example Using Gasoline Data",
        "References"
      ],
      "created": "2016-12-31 18:29:15",
      "modified": "2020-01-15 00:52:05",
      "commits": 13
    },
    {
      "source": "binomial.Rmd",
      "filename": "binomial.html",
      "title": "Estimating Generalized Linear Models for Binary and Binomial Data with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "Priors",
        "Posterior",
        "Logistic Regression Example",
        "Conditional Logit Models",
        "Binomial Models",
        "Going Further",
        "References"
      ],
      "created": "2015-09-03 18:55:03",
      "modified": "2025-09-29 14:51:55",
      "commits": 39
    },
    {
      "source": "continuous.Rmd",
      "filename": "continuous.html",
      "title": "Estimating Generalized Linear Models for Continuous Data with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "Priors",
        "Posterior",
        "Linear Regression Example",
        "Model comparison",
        "The posterior predictive distribution",
        "Graphical posterior predictive checks",
        "Generating predictions",
        "Gamma Regression Example",
        "References"
      ],
      "created": "2015-12-07 17:14:22",
      "modified": "2025-09-29 14:51:55",
      "commits": 26
    },
    {
      "source": "count.Rmd",
      "filename": "count.html",
      "title": "Estimating Generalized Linear Models for Count Data with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "Priors",
        "Posterior",
        "Poisson and Negative Binomial Regression Example",
        "References"
      ],
      "created": "2015-09-04 18:10:15",
      "modified": "2025-09-29 14:51:55",
      "commits": 40
    },
    {
      "source": "glmer.Rmd",
      "filename": "glmer.html",
      "title": "Estimating Generalized (Non-)Linear Models with Group-Specific Terms with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "GLMs with group-specific terms",
        "Priors on covariance matrices",
        "Overview",
        "Details",
        "Comparison with lme4",
        "Advantage: better uncertainty estimates",
        "Advantage: incorporate prior information",
        "Disadvantage: speed",
        "Relationship to glmer",
        "Relationship to gamm4",
        "Relationship to nlmer",
        "Conclusion"
      ],
      "created": "2016-01-08 17:14:15",
      "modified": "2021-05-07 23:23:17",
      "commits": 21
    },
    {
      "source": "jm.Rmd",
      "filename": "jm.html",
      "title": "Estimating Joint Models for Longitudinal and Time-to-Event Data with rstanarm",
      "author": "Sam Brilleman",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Preamble",
        "Introduction",
        "Technical details",
        "Model formulation",
        "Longitudinal submodel(s)",
        "Event submodel",
        "Association structures",
        "Assumptions",
        "Log posterior distribution",
        "Model predictions",
        "Individual-specific predictions for in-sample individuals (for $0 \\leq t \\leq T_i$)",
        "Individual-specific predictions for in-sample individuals (for $t > C_i$)",
        "Individual-specific predictions for out-of-sample individuals (i.e. dynamic predictions)",
        "Population-level (i.e. marginal) predictions",
        "Standardised survival probabilities",
        "Model extensions",
        "Delayed entry (left-truncation)",
        "Multilevel clustering",
        "Model comparison",
        "LOO/WAIC in the context of joint models",
        "Usage examples",
        "Dataset used in the examples",
        "Fitting the models",
        "Univariate joint model (current value association structure)",
        "Univariate joint model (current value and current slope association structure)",
        "Multivariate joint model (current value association structures)",
        "Posterior predictions",
        "Predicted individual-specific longitudinal trajectory for in-sample individuals",
        "Predicted individual-specific survival curves for in-sample individuals",
        "Combined plot of longitudinal trajectories and survival curves",
        "Predicted individual-specific longitudinal trajectory and survival curve for out-of-sample individuals (i.e. dynamic predictions)",
        "Predicted population-level longitudinal trajectory",
        "Standardised survival curves",
        "References"
      ],
      "created": "2017-11-11 21:47:07",
      "modified": "2022-03-16 19:55:10",
      "commits": 11
    },
    {
      "source": "lm.Rmd",
      "filename": "lm.html",
      "title": "Estimating Regularized Linear Models with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "QR Decomposition",
        "Priors",
        "Posterior",
        "Example",
        "Alternative Approach",
        "Conclusion",
        "References"
      ],
      "created": "2015-08-30 21:03:13",
      "modified": "2020-01-15 00:52:05",
      "commits": 31
    },
    {
      "source": "polr.Rmd",
      "filename": "polr.html",
      "title": "Estimating Ordinal Regression Models with rstanarm",
      "author": "Jonah Gabry and Ben Goodrich",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Likelihood",
        "Priors",
        "Example",
        "Conclusion"
      ],
      "created": "2015-09-02 20:46:44",
      "modified": "2020-01-15 00:52:05",
      "commits": 23
    }
  ],
  "_score": 16.278553842483802,
  "_indexed": false,
  "_nocasepkg": "rstanarm",
  "_universes": [
    "r-multiverse"
  ],
  "_indexurl": "https://stan-dev.r-universe.dev/rstanarm",
  "_binaries": [
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "2.32.2",
      "date": "2026-03-23T09:40:02.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "e2c3030d49bea06e517628a21020c41b072017799d5f9f0eddb0432f67445af7",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "2.32.2",
      "date": "2026-03-23T09:39:45.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "3cdefee038b0576648c058a777a970a607735b91d2a33f67b3c997da4052cc64",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.5.3",
      "os": "linux",
      "version": "2.32.2",
      "date": "2026-03-23T09:39:32.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "fa389860d0324fb08da93a88ef310a56622b3c54cc41b5999c505849e3e5c8df",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.5.3",
      "os": "linux",
      "version": "2.32.2",
      "date": "2026-03-23T09:39:41.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "ccb108a692dcac2a05ea264e4e98521fb856a0ced7eb676505a3ceefeda5b2c5",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "2.32.2",
      "date": "2026-03-23T09:41:54.000Z",
      "arch": "aarch64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "cfb96379c633a7d59dcb4bc9c25b6de38301bea46e65de9327be49297664cdad",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "2.32.2",
      "date": "2026-03-23T09:42:26.000Z",
      "arch": "x86_64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "630c6f61904bfb957d19ddf33e0b11ccd1d39fd16338aedcbc4ef9df702cf01f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "2.32.2",
      "date": "2026-03-23T09:41:28.000Z",
      "arch": "aarch64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "d198fd32e7b7979327a50c87cb46004671df8f068ca897e23ce724739ebcc69e",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "2.32.2",
      "date": "2026-03-23T09:42:49.000Z",
      "arch": "x86_64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "7f05ced8a73deb5feb8dba9b1381db12a5e1db6e0f6afab3e781754952402d83",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "2.32.2",
      "date": "2026-03-23T09:42:04.000Z",
      "arch": "x86_64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "70ccc8c3779883cade56d8238bbb35e2ed43338dd96b61650e8143af7fed52ba",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "2.32.2",
      "date": "2026-03-23T09:38:15.000Z",
      "arch": "x86_64",
      "commit": "aabb521eeb7a53eadc7178ec2ffb8f1e11e8c242",
      "fileid": "6d5deb16599edd1c674f351b13234b4aea92dcd5d189b3cb9f40e9da51cc0fc2",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/r-multiverse/actions/runs/23429628710"
    }
  ]
}