Load Random Effect Samples from JSON

Load a container of random effect samples from json

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 stochtree.ai

Usage

loadRandomEffectSamplesJson(json_object, json_rfx_num)

Arguments

json_object

Object 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 <- saveBARTModelToJson(bart_model)
rfx_samples <- loadRandomEffectSamplesJson(bart_json, 0)