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  "Package": "dbarts",
  "Version": "0.9-34",
  "Date": "2026-06-19",
  "Title": "Discrete Bayesian Additive Regression Trees Sampler",
  "Authors@R": "c(\nperson(\"Vincent\", \"Dorie\", role = c(\"aut\", \"cre\"), email = \"vdorie@gmail.com\", comment = c(ORCID = \"0000-0002-9576-3064\")),\nperson(\"Hugh\", \"Chipman\", role = \"aut\", email = \"hugh.chipman@gmail.com\"),\nperson(\"Robert\", \"McCulloch\", role = \"aut\", email = \"robert.mcculloch1@gmail.com\"),\nperson(\"Armon\", \"Dadgar\", role = \"ctb\", comment = \"adaptive radix tree\"),\nperson(\"R Core Team\", role = \"ctb\", comment = \"basis of RNG\"),\nperson(\"Guido U\", \"Draheim\", role = \"ctb\", comment = \"ax_check_compile_flag.m4\"),\nperson(\"Maarten\", \"Bosmans\", role = \"ctb\", comment = \"ax_check_compile_flag.m4\"),\nperson(\"Christophe\", \"Tournayre\", role = \"ctb\", comment = \"ax_compiler_ext.m4, ax_ext.m4\"),\nperson(\"Michael\", \"Petch\", role = \"ctb\", comment = \"ax_compiler_ext.m4, ax_ext.m4, ax_gcc_x86_avx_xgetbv.m4, ax_gcc_x86_cpuid.m4\"),\nperson(\"Rafael\", \"de Lucena Valle\", role = \"ctb\", comment = \"ax_compiler_ext.m4, ax_ext.m4\"),\nperson(\"Steven G.\", \"Johnson\", role = \"ctb\", comment = c(\"ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4, ax_pthread.m4\", ORCID = \"0000-0001-7327-4967\")),\nperson(\"Matteo\", \"Frigo\", role = \"ctb\", comment = \"ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4\"),\nperson(\"John\", \"Zaitseff\", role = \"ctb\", comment = \"ax_compiler_vendor.m4\"),\nperson(\"Todd\", \"Veldhuizen\", role = \"ctb\", comment = \"ax_cxx_namespace_std.m4\"),\nperson(\"Luc\", \"Maisonobe\", role = \"ctb\", comment = \"ax_cxx_namespace_std.m4\"),\nperson(\"Scott\", \"Pakin\", role = \"ctb\", comment = c(\"ax_func_posix_memalign.m4\", ORCID = \"0000-0002-5220-1985\")),\nperson(\"Daniel\", \"Richard G.\", role = \"ctb\", comment = \"ax_pthread.m4\"))",
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  "Description": "Fits Bayesian additive regression trees (BART; Chipman,\nGeorge, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while\nallowing the updating of predictors or response so that BART\ncan be incorporated as a conditional model in a\nGibbs/Metropolis-Hastings sampler. Also serves as a drop-in\nreplacement for package 'BayesTree'.",
  "License": "GPL (>= 2)",
  "NeedsCompilation": "yes",
  "Biarch": "yes",
  "URL": "https://github.com/vdorie/dbarts",
  "BugReports": "https://github.com/vdorie/dbarts/issues",
  "Repository": "https://vdorie.r-universe.dev",
  "Date/Publication": "2026-07-02 16:15:37 UTC",
  "RemoteUrl": "https://github.com/vdorie/dbarts",
  "RemoteRef": "HEAD",
  "RemoteSha": "e7ebf5205a07df96f394407f0a16773b2762a368",
  "Packaged": {
    "Date": "2026-07-02 17:04:11 UTC",
    "User": "root"
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  "Author": "Vincent Dorie [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-9576-3064>),\nHugh Chipman [aut],\nRobert McCulloch [aut],\nArmon Dadgar [ctb] (adaptive radix tree),\nR Core Team [ctb] (basis of RNG),\nGuido U Draheim [ctb] (ax_check_compile_flag.m4),\nMaarten Bosmans [ctb] (ax_check_compile_flag.m4),\nChristophe Tournayre [ctb] (ax_compiler_ext.m4, ax_ext.m4),\nMichael Petch [ctb] (ax_compiler_ext.m4, ax_ext.m4,\nax_gcc_x86_avx_xgetbv.m4, ax_gcc_x86_cpuid.m4),\nRafael de Lucena Valle [ctb] (ax_compiler_ext.m4, ax_ext.m4),\nSteven G. Johnson [ctb] (ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4,\nax_pthread.m4, ORCID: <https://orcid.org/0000-0001-7327-4967>),\nMatteo Frigo [ctb] (ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4),\nJohn Zaitseff [ctb] (ax_compiler_vendor.m4),\nTodd Veldhuizen [ctb] (ax_cxx_namespace_std.m4),\nLuc Maisonobe [ctb] (ax_cxx_namespace_std.m4),\nScott Pakin [ctb] (ax_func_posix_memalign.m4, ORCID:\n<https://orcid.org/0000-0002-5220-1985>),\nDaniel Richard G. [ctb] (ax_pthread.m4)",
  "Maintainer": "Vincent Dorie <vdorie@gmail.com>",
  "_user": "vdorie",
  "_type": "src",
  "_file": "dbarts_0.9-34.tar.gz",
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    "message": "Count new data through fitted trees via getTrees(newdata=)\n\ngetTrees and extract(., \"trees\") accept a newdata matrix, routing those observations through each tree so the n column counts them instead of the training data. Validated and coded as in predict.\n\nAdds BARTFit::getFlattenedTreesCountingData and the C API dbarts_getTreesCountingData; getFlattenedTrees keeps its training-only signature. dbarts_getTrees exports the useLiveTrees flag behind getTrees(current = TRUE).\n\nA shared flattenTrees helper routes observations once via an in-place index partition, replacing the per-node std::set descent and serving live and saved trees alike.\n",
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
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    "extra/NEWS.html",
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      "date": "2020-06-12"
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      "date": "2022-03-29"
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  ],
  "_exports": [
    "bart",
    "bart2",
    "dbarts",
    "dbartsControl",
    "dbartsData",
    "extract",
    "guessNumCores",
    "makeind",
    "makeModelMatrixFromDataFrame",
    "makeTestModelMatrix",
    "pd2bart",
    "pdbart",
    "rbart_vi",
    "updatePredictorPerObservationJointly",
    "xbart"
  ],
  "_help": [
    {
      "page": "bart",
      "title": "Bayesian Additive Regression Trees",
      "topics": [
        "bart",
        "bart2",
        "extract",
        "extract.bart",
        "fitted.bart",
        "plot.bart",
        "predict.bart",
        "residuals.bart"
      ]
    },
    {
      "page": "dbarts",
      "title": "Discrete Bayesian Additive Regression Trees Sampler",
      "topics": [
        "dbarts"
      ]
    },
    {
      "page": "dbartsControl",
      "title": "Discrete Bayesian Additive Regression Trees Sampler Control",
      "topics": [
        "dbartsControl"
      ]
    },
    {
      "page": "dbartsData",
      "title": "Discrete Bayesian Additive Regression Trees Sampler Data",
      "topics": [
        "dbartsData"
      ]
    },
    {
      "page": "dbartsSampler-class",
      "title": "Class \"dbartsSampler\" of Discrete Bayesian Additive Regression Trees Sampler",
      "topics": [
        "dbartsSampler",
        "dbartsSampler-class",
        "\\S4method{copy}{dbartsSampler}",
        "\\S4method{getTrees}{dbartsSampler}",
        "\\S4method{plotTree}{dbartsSampler}",
        "\\S4method{predict}{dbartsSampler}",
        "\\S4method{printTrees}{dbartsSampler}",
        "\\S4method{run}{dbartsSampler}",
        "\\S4method{sampleNodeParametersFromPrior}{dbartsSampler}",
        "\\S4method{sampleTreesFromPrior}{dbartsSampler}",
        "\\S4method{setControl}{dbartsSampler}",
        "\\S4method{setCutPoints}{dbartsSampler}",
        "\\S4method{setData}{dbartsSampler}",
        "\\S4method{setModel}{dbartsSampler}",
        "\\S4method{setOffset}{dbartsSampler}",
        "\\S4method{setPredictor}{dbartsSampler}",
        "\\S4method{setResponse}{dbartsSampler}",
        "\\S4method{setSigma}{dbartsSampler}",
        "\\S4method{setTestOffset}{dbartsSampler}",
        "\\S4method{setTestPredictorAndOffset}{dbartsSampler}",
        "\\S4method{setTestPredictor}{dbartsSampler}",
        "\\S4method{show}{dbartsSampler}",
        "\\S4method{startThreads}{dbartsSampler}",
        "\\S4method{stopThreads}{dbartsSampler}"
      ]
    },
    {
      "page": "guessNumCores",
      "title": "Guess Number of Cores",
      "topics": [
        "guessNumCores"
      ]
    },
    {
      "page": "makeind",
      "title": "Make Model Matrix from Data Frame",
      "topics": [
        "makeind",
        "makeModelMatrixFromDataFrame",
        "makeTestModelMatrix"
      ]
    },
    {
      "page": "pdbart",
      "title": "Partial Dependence Plots for BART",
      "topics": [
        "pd2bart",
        "pdbart",
        "plot.pd2bart",
        "plot.pdbart"
      ]
    },
    {
      "page": "rbart",
      "title": "Bayesian Additive Regression Trees with Random Effects",
      "topics": [
        "extract.rbart",
        "fitted.rbart",
        "plot.rbart",
        "predict.rbart",
        "rbart_vi",
        "residuals.rbart"
      ]
    },
    {
      "page": "updatePredictorPerObservationJointly",
      "title": "Jointly Update a Shared Predictor per Observation Across Samplers",
      "topics": [
        "updatePredictorPerObservationJointly"
      ]
    },
    {
      "page": "xbart",
      "title": "Crossvalidation For Bayesian Additive Regression Trees",
      "topics": [
        "xbart"
      ]
    }
  ],
  "_readme": "https://github.com/vdorie/dbarts/raw/HEAD/README.md",
  "_rundeps": [],
  "_sysdeps": [
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      "package": "libstdc++6",
      "source": "gcc",
      "version": "16-20260322-1ubuntu1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
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      "source": "gibbs_sampler_mixture_model.Rmd",
      "filename": "gibbs_sampler_mixture_model.html",
      "title": "Building a Gibbs Sampler with dbarts",
      "author": "Vincent Dorie",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Model",
        "Conditonal Posteriors",
        "Simulated Data",
        "Implementing a Gibbs Sampler",
        "Saveing the sampler",
        "Visualizing the Result",
        "Multiple Threading"
      ],
      "created": "2020-12-21 23:11:31",
      "modified": "2020-12-21 23:11:31",
      "commits": 1
    },
    {
      "source": "working_with_saved_trees.Rmd",
      "filename": "working_with_saved_trees.html",
      "title": "Working with dbarts Saved Trees",
      "author": "Vincent Dorie",
      "engine": "knitr::rmarkdown",
      "headings": [
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        "Model Fitting",
        "Extracting Trees",
        "Flattened Trees",
        "Tree Traversal",
        "Plotting Trees",
        "Getting Tree Predictions",
        "Counts for New Data",
        "Advanced Traversal",
        "References"
      ],
      "created": "2022-01-24 00:31:13",
      "modified": "2026-07-02 16:15:37",
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