createForestModel: Create ForestModel Object

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

Create ForestModel Object

Description

Create a forest model object

This function is intended for advanced use cases in which users require detailed control of sampling algorithms and data structures. Minimal input validation and error checks are performed – users are responsible for providing the correct inputs. For tutorials on the "proper" usage of the stochtree's advanced workflow, we provide several vignettes at https://stochtree.ai/

Usage

createForestModel(forest_dataset, forest_model_config, global_model_config)

Arguments

forest_dataset	ForestDataset object, used to initialize forest sampling data structures
forest_model_config	ForestModelConfig object containing forest model parameters and settings
global_model_config	GlobalModelConfig object containing global model parameters and settings

Value

ForestModel object

Examples

num_trees <- 100
n <- 100
p <- 10
alpha <- 0.95
beta <- 2.0
min_samples_leaf <- 2
max_depth <- 10
feature_types <- as.integer(rep(0, p))
X <- matrix(runif(n*p), ncol = p)
forest_dataset <- createForestDataset(X)
forest_model_config <- createForestModelConfig(feature_types=feature_types,
                                               num_trees=num_trees, num_features=p,
                                               num_observations=n, alpha=alpha, beta=beta,
                                               min_samples_leaf=min_samples_leaf,
                                               max_depth=max_depth, leaf_model_type=1)
global_model_config <- createGlobalModelConfig(global_error_variance=1.0)
forest_model <- createForestModel(forest_dataset, forest_model_config, global_model_config)

stochtree documentation built on April 29, 2026, 1:08 a.m.