Package index • stochtree

Supervised learning

High-level functionality for training supervised Bayesian tree ensembles (BART, XBART)

bart(): Run BART for Supervised Learning
predict(<bartmodel>): Predict From a BART Model
print(<bartmodel>): Summarize a BART Model
summary(<bartmodel>): Summarize the BART model fit and sampled terms.
plot(<bartmodel>): Plot BART Model Fit.
extract_parameter(<bartmodel>): Extract BART Parameter Samples.
getRandomEffectSamples(<bartmodel>): Extract Random Effects Samples
compute_bart_posterior_interval(): Compute BART Posterior Credible Intervals
compute_contrast_bart_model(): Compute Contrast for BART Model
sample_bart_posterior_predictive(): Sample BART Posterior Predictive

Causal inference

High-level functionality for estimating causal effects using Bayesian tree ensembles (BCF, XBCF)

bcf(): Run BCF for Causal Effect Estimation
predict(<bcfmodel>): Predict From BCF Model
print(<bcfmodel>): Print Summary of BCF Model
summary(<bcfmodel>): Summarize BCF Model
plot(<bcfmodel>): Plot BCF Model
extract_parameter(<bcfmodel>): Extract BCF Parameter Samples
getRandomEffectSamples(<bcfmodel>): Extract Random Effect Samples from BCF Model
compute_bcf_posterior_interval(): Compute BCF Posterior Credible Intervals
compute_contrast_bcf_model(): Compute Contrast for BCF Model
sample_bcf_posterior_predictive(): Sample BCF Posterior Predictive

Low-level functionality

Serialization

Classes and functions for converting sampling artifacts to JSON and saving to disk

CppJson: JSON C++ Object Wrapper
createCppJson(): Create CppJson Object
createCppJsonFile(): Create CppJson Object from File
createCppJsonString(): Create CppJson Object from String
loadForestContainerJson(): Load Forest Samples from JSON
loadForestContainerCombinedJson(): Combine JSON Model Objects into ForestSamples
loadForestContainerCombinedJsonString(): Combine JSON Strings into ForestSamples
loadVectorJson(): Load Vector from JSON
loadScalarJson(): Load Scalar from JSON
loadRandomEffectSamplesJson(): Load Random Effect Samples from JSON
loadRandomEffectSamplesCombinedJson(): Combine JSON Model Objects into RandomEffectSamples
loadRandomEffectSamplesCombinedJsonString(): Combine JSON Strings into RandomEffectSamples
saveBARTModelToJson(): Convert BART Model to JSON
saveBARTModelToJsonFile(): Save BART Model to JSON File
saveBARTModelToJsonString(): Convert BART Model to JSON String
createBARTModelFromJson(): Convert JSON to BART Model
createBARTModelFromJsonFile(): Convert JSON File to BART Model
createBARTModelFromJsonString(): Convert JSON String to BART Model
createBARTModelFromCombinedJson(): Convert JSON List to Single BART Model
createBARTModelFromCombinedJsonString(): Convert JSON String List to Single BART Model
saveBCFModelToJson(): Convert BCF Model to JSON
saveBCFModelToJsonFile(): Save BCF Model to JSON File
saveBCFModelToJsonString(): Convert BCF Model to JSON String
createBCFModelFromJsonFile(): Convert JSON File to BCF Model
createBCFModelFromJsonString(): Convert JSON String to BCF Model
createBCFModelFromJson(): Convert JSON to BCF Model
createBCFModelFromCombinedJson(): Convert JSON List to BCF Model
createBCFModelFromCombinedJsonString(): Convert JSON String List to BCF Model

Data

Classes and functions for preparing data for sampling algorithms

ForestDataset: Forest Dataset C++ Wrapper
createForestDataset(): Create ForestDataset Object
Outcome: Outcome Data C++ Wrapper
createOutcome(): Create Outcome Object
RandomEffectsDataset: Random Effects Dataset C++ Wrapper
createRandomEffectsDataset(): Create RandomEffectsDataset Object
preprocessTrainData(): Preprocess Covariates for Model Training
preprocessPredictionData(): Preprocess Covariates for Model Prediction
convertPreprocessorToJson(): Convert Covariate Preprocessor to CppJson
savePreprocessorToJsonString(): Convert Covariate Preprocessor to JSON String
createPreprocessorFromJson(): Reload Covariate Preprocessor from JSON String
createPreprocessorFromJsonString(): Reload Covariate Preprocessor from JSON String

Forest

Classes and functions for constructing and persisting forests

Forest: Forest C++ Wrapper
createForest(): Create Forest Object
ForestModel: Forest Model C++ Wrapper
createForestModel(): Create ForestModel Object
ForestSamples: Forest Container C++ Wrapper
createForestSamples(): Create ForestSamples Object
ForestModelConfig: Forest Model Configuration Object
createForestModelConfig(): Create ForestModelConfig Object
GlobalModelConfig: Global Model Configuration Object
createGlobalModelConfig(): Create GlobalModelConfig Object
CppRNG: Random Number Generator C++ Wrapper
createCppRNG(): Create CppRNG Object
calibrateInverseGammaErrorVariance(): Calibrate Inverse Gamma Prior
computeForestMaxLeafIndex(): Query Forest Max Leaf Index
computeForestLeafIndices(): Query Forest Leaf Indices
computeForestLeafVariances(): Query Forest Leaf Scale Parameters
resetActiveForest(): Reset Active Forest
resetForestModel(): Reset Forest Model

Random Effects

Classes and functions for constructing and persisting random effects terms

RandomEffectSamples: Random Effect Container C++ Wrapper
createRandomEffectSamples(): Create RandomEffectSamples Object
RandomEffectsModel: Random Effects Model C++ Wrapper
createRandomEffectsModel(): Create RandomEffectsModel Object
RandomEffectsTracker: Random Effects Tracker C++ Wrapper
createRandomEffectsTracker(): Create RandomEffectsTracker Object
getRandomEffectSamples(): Extract Random Effect Samples Generic Function
sampleGlobalErrorVarianceOneIteration(): Sample Global Error Variance
sampleLeafVarianceOneIteration(): Sample Leaf Scale
resetRandomEffectsModel(): Reset RandomEffectsModel Object
resetRandomEffectsTracker(): Reset RandomEffectsTracker Object
rootResetRandomEffectsModel(): Reset RandomEffectsModel Object to Default State
rootResetRandomEffectsTracker(): Reset RandomEffectsTracker Object to Default State

Utilities

Miscellaneous “utility” classes and functions

sample_without_replacement(): Sample Without Replacement
extract_parameter(): Extract Parameter Samples Generic Function

Package info

High-level package details

stochtree stochtree-package: stochtree: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference