stochtree0.1.1 package

Run the BART algorithm for supervised learning.

Run the Bayesian Causal Forest (BCF) algorithm for regularized causal ...

Calibrate the scale parameter on an inverse gamma prior for the global...

Compute vector of forest leaf indices

Compute vector of forest leaf scale parameters

Compute and return the largest possible leaf index computable by `comp...

Convert the persistent aspects of a covariate preprocessor to (in-memo...

Class that stores draws from an random ensemble of decision trees

Class that wraps a C++ random number generator (for reproducibility)

Convert a list of (in-memory) JSON representations of a BART model to ...

Convert a list of (in-memory) JSON strings that represent BART models ...

Convert an (in-memory) JSON representation of a BART model to a BART m...

Convert a JSON file containing sample information on a trained BART mo...

Convert a JSON string containing sample information on a trained BART ...

Convert a list of (in-memory) JSON strings that represent BCF models t...

Convert a list of (in-memory) JSON strings that represent BCF models t...

Convert an (in-memory) JSON representation of a BCF model to a BCF mod...

Convert a JSON file containing sample information on a trained BCF mod...

Convert a JSON string containing sample information on a trained BCF m...

Create a new (empty) C++ Json object

Create a C++ Json object from a Json file

Create a C++ Json object from a Json string

Create an R class that wraps a C++ random number generator

Create a forest

Create a forest dataset object

Create a forest model object

Create a forest model config object

Create a container of forest samples

Create a global model config object

Create an outcome object

Reload a covariate preprocessor object from a JSON string containing a...

Reload a covariate preprocessor object from a JSON string containing a...

Create a RandomEffectSamples object

Create a random effects dataset object

Create a RandomEffectsModel object

Create a RandomEffectsTracker object

Class that stores a single ensemble of decision trees (often treated a...

Dataset used to sample a forest

Class that defines and samples a forest model

Object used to get / set parameters and other model configuration opti...

Class that stores draws from an random ensemble of decision trees

Extract raw sample values for each of the random effect parameter term...

Extract raw sample values for each of the random effect parameter term...

Generic function for extracting random effect samples from a model obj...

Object used to get / set global parameters and other global model conf...

Combine multiple JSON model objects containing forests (with the same ...

Combine multiple JSON strings representing model objects containing fo...

Load a container of forest samples from json

Combine multiple JSON model objects containing random effects (with th...

Combine multiple JSON strings representing model objects containing ra...

Load a container of random effect samples from json

Load a scalar from json

Load a vector from json

Outcome / partial residual used to sample an additive model.

Predict from a sampled BART model on new data

Predict from a sampled BCF model on new data

Preprocess covariates. DataFrames will be preprocessed based on their ...

Preprocess covariates. DataFrames will be preprocessed based on their ...

Class that wraps the "persistent" aspects of a C++ random effects mode...

Dataset used to sample a random effects model

The core "model" class for sampling random effects.

Class that defines a "tracker" for random effects models, most notably...

Reset an active forest, either from a specific forest in a `ForestCont...

Re-initialize a forest model (tracking data structures) from a specifi...

Reset a RandomEffectsModel object based on the parameters indexed by...

Reset a RandomEffectsTracker object based on the parameters indexed ...

Reset a RandomEffectsModel object to its "default" state

Reset a RandomEffectsTracker object to its "default" state

Sample one iteration of the (inverse gamma) global variance model

Sample one iteration of the leaf parameter variance model (only for un...

Convert the persistent aspects of a BART model to (in-memory) JSON

Convert the persistent aspects of a BART model to (in-memory) JSON and...

Convert the persistent aspects of a BART model to (in-memory) JSON str...

Convert the persistent aspects of a BCF model to (in-memory) JSON

Convert the persistent aspects of a BCF model to (in-memory) JSON and ...

Convert the persistent aspects of a BCF model to (in-memory) JSON stri...

Convert the persistent aspects of a covariate preprocessor to (in-memo...

stochtree: Stochastic Tree Ensembles (XBART and BART) for Supervised L...