rootResetRandomEffectsModel: Reset a 'RandomEffectsModel' object to its "default" state

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

Reset a RandomEffectsModel object to its "default" state

Description

Reset a RandomEffectsModel object to its "default" state

Usage

rootResetRandomEffectsModel(
  rfx_model,
  alpha_init,
  xi_init,
  sigma_alpha_init,
  sigma_xi_init,
  sigma_xi_shape,
  sigma_xi_scale
)

Arguments

rfx_model	Object of type RandomEffectsModel.
alpha_init	Initial value of the "working parameter".
xi_init	Initial value of the "group parameters".
sigma_alpha_init	Initial value of the "working parameter" scale parameter.
sigma_xi_init	Initial value of the "group parameters" scale parameter.
sigma_xi_shape	Shape parameter for the inverse gamma variance model on the group parameters.
sigma_xi_scale	Scale parameter for the inverse gamma variance model on the group parameters.

Value

None

Examples

n <- 100
p <- 10
rfx_group_ids <- sample(1:2, size = n, replace = TRUE)
rfx_basis <- matrix(rep(1.0, n), ncol=1)
rfx_dataset <- createRandomEffectsDataset(rfx_group_ids, rfx_basis)
y <- (-2*(rfx_group_ids==1)+2*(rfx_group_ids==2)) + rnorm(n)
y_std <- (y-mean(y))/sd(y)
outcome <- createOutcome(y_std)
rng <- createCppRNG(1234)
num_groups <- length(unique(rfx_group_ids))
num_components <- ncol(rfx_basis)
rfx_model <- createRandomEffectsModel(num_components, num_groups)
rfx_tracker <- createRandomEffectsTracker(rfx_group_ids)
rfx_samples <- createRandomEffectSamples(num_components, num_groups, rfx_tracker)
alpha_init <- rep(1,num_components)
xi_init <- matrix(rep(alpha_init, num_groups),num_components,num_groups)
sigma_alpha_init <- diag(1,num_components,num_components)
sigma_xi_init <- diag(1,num_components,num_components)
sigma_xi_shape <- 1
sigma_xi_scale <- 1
rfx_model$set_working_parameter(alpha_init)
rfx_model$set_group_parameters(xi_init)
rfx_model$set_working_parameter_cov(sigma_alpha_init)
rfx_model$set_group_parameter_cov(sigma_xi_init)
rfx_model$set_variance_prior_shape(sigma_xi_shape)
rfx_model$set_variance_prior_scale(sigma_xi_scale)
for (i in 1:3) {
    rfx_model$sample_random_effect(rfx_dataset=rfx_dataset, residual=outcome, 
                                   rfx_tracker=rfx_tracker, rfx_samples=rfx_samples, 
                                   keep_sample=TRUE, global_variance=1.0, rng=rng)
}
rootResetRandomEffectsModel(rfx_model, alpha_init, xi_init, sigma_alpha_init,
                            sigma_xi_init, sigma_xi_shape, sigma_xi_scale)

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