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  "Title": "Stochastic Tree Ensembles (XBART and BART) for Supervised\nLearning and Causal Inference",
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  "Authors@R": "c(\nperson(\"Drew\", \"Herren\", email = \"drewherrenopensource@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-4109-6611\")),\nperson(\"Richard\", \"Hahn\", role = \"aut\"),\nperson(\"Jared\", \"Murray\", role = \"aut\"),\nperson(\"Carlos\", \"Carvalho\", role = \"aut\"),\nperson(\"Jingyu\", \"He\", role = \"aut\"),\nperson(\"Pedro\", \"Lima\", role = \"ctb\"),\nperson(\"Entejar\", \"Alam\", role = \"ctb\"),\nperson(\"stochtree\", \"contributors\", role = c(\"cph\")),\nperson(\"Eigen\", \"contributors\", role = c(\"cph\"), comment = \"C++ source uses the Eigen library for matrix operations, see inst/COPYRIGHTS\"),\nperson(\"xgboost\", \"contributors\", role = c(\"cph\"), comment = \"C++ tree code and related operations include or are inspired by code from the xgboost library, see inst/COPYRIGHTS\"),\nperson(\"treelite\", \"contributors\", role = c(\"cph\"), comment = \"C++ tree code and related operations include or are inspired by code from the treelite library, see inst/COPYRIGHTS\"),\nperson(\"Microsoft\", \"Corporation\", role = c(\"cph\"), comment = \"C++ I/O and various project structure code include or are inspired by code from the LightGBM library, which is a copyright of Microsoft, see inst/COPYRIGHTS\"),\nperson(\"Niels\", \"Lohmann\", role = c(\"cph\"), comment = \"C++ source uses the JSON for Modern C++ library for JSON operations, see inst/COPYRIGHTS\"),\nperson(\"Daniel\", \"Lemire\", role = c(\"cph\"), comment = \"C++ source uses the fast_double_parser library internally, see inst/COPYRIGHTS\"),\nperson(\"Victor\", \"Zverovich\", role = c(\"cph\"), comment = \"C++ source uses the fmt library internally, see inst/COPYRIGHTS\")\n)",
  "Copyright": "Copyright details for stochtree's C++ dependencies, which\nare vendored along with the core stochtree source code, are\ndetailed in inst/COPYRIGHTS",
  "Description": "Flexible stochastic tree ensemble software. Robust\nimplementations of Bayesian Additive Regression Trees (BART)\n(Chipman, George, McCulloch (2010) <doi:10.1214/09-AOAS285>)\nfor supervised learning and Bayesian Causal Forests (BCF)\n(Hahn, Murray, Carvalho (2020) <doi:10.1214/19-BA1195>) for\ncausal inference. Enables model serialization and parallel\nsampling and provides a low-level interface for custom\nstochastic forest samplers. Includes the grow-from-root\nalgorithm for accelerated forest sampling (He and Hahn (2021)\n<doi:10.1080/01621459.2021.1942012>), a log-linear leaf model\nfor forest-based heteroskedasticity (Murray (2020)\n<doi:10.1080/01621459.2020.1813587>), and the cloglog BART\nmodel of Alam and Linero (2025) <doi:10.48550/arXiv.2502.00606>\nfor ordinal outcomes.",
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  "BugReports": "https://github.com/StochasticTree/stochtree/issues",
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  "Repository": "https://stochastictree.r-universe.dev",
  "Date/Publication": "2026-06-05 19:53:38 UTC",
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  "Author": "Drew Herren [aut, cre] (ORCID: <https://orcid.org/0000-0003-4109-6611>),\nRichard Hahn [aut],\nJared Murray [aut],\nCarlos Carvalho [aut],\nJingyu He [aut],\nPedro Lima [ctb],\nEntejar Alam [ctb],\nstochtree contributors [cph],\nEigen contributors [cph] (C++ source uses the Eigen library for matrix\noperations, see inst/COPYRIGHTS),\nxgboost contributors [cph] (C++ tree code and related operations\ninclude or are inspired by code from the xgboost library, see\ninst/COPYRIGHTS),\ntreelite contributors [cph] (C++ tree code and related operations\ninclude or are inspired by code from the treelite library, see\ninst/COPYRIGHTS),\nMicrosoft Corporation [cph] (C++ I/O and various project structure code\ninclude or are inspired by code from the LightGBM library, which is\na copyright of Microsoft, see inst/COPYRIGHTS),\nNiels Lohmann [cph] (C++ source uses the JSON for Modern C++ library\nfor JSON operations, see inst/COPYRIGHTS),\nDaniel Lemire [cph] (C++ source uses the fast_double_parser library\ninternally, see inst/COPYRIGHTS),\nVictor Zverovich [cph] (C++ source uses the fmt library internally, see\ninst/COPYRIGHTS)",
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    "bart",
    "bcf",
    "calibrateInverseGammaErrorVariance",
    "computeBARTPosteriorInterval",
    "computeBCFPosteriorInterval",
    "computeContrastBARTModel",
    "computeContrastBCFModel",
    "computeForestLeafIndices",
    "computeForestLeafVariances",
    "computeForestMaxLeafIndex",
    "createBARTModelFromCombinedJson",
    "createBARTModelFromCombinedJsonString",
    "createBARTModelFromJson",
    "createBARTModelFromJsonFile",
    "createBARTModelFromJsonString",
    "createBCFModelFromCombinedJson",
    "createBCFModelFromCombinedJsonString",
    "createBCFModelFromJson",
    "createBCFModelFromJsonFile",
    "createBCFModelFromJsonString",
    "createCppJson",
    "createCppJsonFile",
    "createCppJsonString",
    "createCppRNG",
    "createForest",
    "createForestDataset",
    "createForestModel",
    "createForestModelConfig",
    "createForestSamples",
    "createGlobalModelConfig",
    "createOutcome",
    "createPreprocessorFromJson",
    "createPreprocessorFromJsonString",
    "createRandomEffectSamples",
    "createRandomEffectsDataset",
    "createRandomEffectsModel",
    "createRandomEffectsTracker",
    "extractParameter",
    "getRandomEffectSamples",
    "loadForestContainerCombinedJson",
    "loadForestContainerCombinedJsonString",
    "loadForestContainerJson",
    "loadRandomEffectSamplesCombinedJson",
    "loadRandomEffectSamplesCombinedJsonString",
    "loadRandomEffectSamplesJson",
    "loadScalarJson",
    "loadVectorJson",
    "OutcomeModel",
    "preprocessPredictionData",
    "preprocessTrainData",
    "resetActiveForest",
    "resetForestModel",
    "resetRandomEffectsModel",
    "resetRandomEffectsTracker",
    "rootResetRandomEffectsModel",
    "rootResetRandomEffectsTracker",
    "sample_without_replacement",
    "sampleBARTPosteriorPredictive",
    "sampleBCFPosteriorPredictive",
    "sampleGlobalErrorVarianceOneIteration",
    "sampleLeafVarianceOneIteration",
    "saveBARTModelToJson",
    "saveBARTModelToJsonFile",
    "saveBARTModelToJsonString",
    "saveBCFModelToJson",
    "saveBCFModelToJsonFile",
    "saveBCFModelToJsonString",
    "savePreprocessorToJson",
    "savePreprocessorToJsonString"
  ],
  "_help": [
    {
      "page": "stochtree-package",
      "title": "stochtree: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference",
      "topics": [
        "stochtree-package",
        "stochtree"
      ]
    },
    {
      "page": "bart",
      "title": "Run BART for Supervised Learning",
      "topics": [
        "bart"
      ]
    },
    {
      "page": "BARTSerialization",
      "title": "BART Serialization Routines",
      "topics": [
        "BARTSerialization",
        "createBARTModelFromCombinedJson",
        "createBARTModelFromCombinedJsonString",
        "createBARTModelFromJson",
        "createBARTModelFromJsonFile",
        "createBARTModelFromJsonString",
        "saveBARTModelToJson",
        "saveBARTModelToJsonFile",
        "saveBARTModelToJsonString"
      ]
    },
    {
      "page": "bcf",
      "title": "Run BCF for Causal Effect Estimation",
      "topics": [
        "bcf"
      ]
    },
    {
      "page": "BCFSerialization",
      "title": "BCF Serialization Routines",
      "topics": [
        "BCFSerialization",
        "createBCFModelFromCombinedJson",
        "createBCFModelFromCombinedJsonString",
        "createBCFModelFromJson",
        "createBCFModelFromJsonFile",
        "createBCFModelFromJsonString",
        "saveBCFModelToJson",
        "saveBCFModelToJsonFile",
        "saveBCFModelToJsonString"
      ]
    },
    {
      "page": "calibrateInverseGammaErrorVariance",
      "title": "Calibrate Inverse Gamma Prior",
      "topics": [
        "calibrateInverseGammaErrorVariance"
      ]
    },
    {
      "page": "computeBARTPosteriorInterval",
      "title": "Compute BART Posterior Credible Intervals",
      "topics": [
        "computeBARTPosteriorInterval"
      ]
    },
    {
      "page": "computeBCFPosteriorInterval",
      "title": "Compute BCF Posterior Credible Intervals",
      "topics": [
        "computeBCFPosteriorInterval"
      ]
    },
    {
      "page": "computeContrastBARTModel",
      "title": "Compute Contrast for BART Model",
      "topics": [
        "computeContrastBARTModel"
      ]
    },
    {
      "page": "computeContrastBCFModel",
      "title": "Compute Contrast for BCF Model",
      "topics": [
        "computeContrastBCFModel"
      ]
    },
    {
      "page": "CppJson",
      "title": "JSON C++ Object Wrapper",
      "topics": [
        "CppJson"
      ]
    },
    {
      "page": "CppRNG",
      "title": "Random Number Generator C++ Wrapper",
      "topics": [
        "CppRNG"
      ]
    },
    {
      "page": "createCppRNG",
      "title": "Create CppRNG Object",
      "topics": [
        "createCppRNG"
      ]
    },
    {
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      "title": "Create Forest Object",
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