loadRandomEffectSamplesCombinedJson: Combine multiple JSON model objects containing random effects...

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

Combine multiple JSON model objects containing random effects (with the same hierarchy / schema) into a single container

Description

Combine multiple JSON model objects containing random effects (with the same hierarchy / schema) into a single container

Usage

loadRandomEffectSamplesCombinedJson(json_object_list, json_rfx_num)

Arguments

json_object_list	List of objects of class CppJson
json_rfx_num	Integer index indicating the position of the random effects term to be unpacked

Value

RandomEffectSamples object

Examples

n <- 100
p <- 10
X <- matrix(runif(n*p), ncol = p)
rfx_group_ids <- sample(1:2, size = n, replace = TRUE)
rfx_basis <- rep(1.0, n)
y <- (-5 + 10*(X[,1] > 0.5)) + (-2*(rfx_group_ids==1)+2*(rfx_group_ids==2)) + rnorm(n)
bart_model <- bart(X_train=X, y_train=y, rfx_group_ids_train=rfx_group_ids,
                   rfx_basis_train = rfx_basis, num_gfr=0, num_mcmc=10)
bart_json <- list(saveBARTModelToJson(bart_model))
rfx_samples <- loadRandomEffectSamplesCombinedJson(bart_json, 0)

stochtree documentation built on April 4, 2025, 2:11 a.m.