Create RandomEffectSamples Object

Create a RandomEffectSamples 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 stochtree.ai

Usage

createRandomEffectSamples(num_components, num_groups, random_effects_tracker)

Arguments

num_components

Number of "components" or bases defining the random effects regression

num_groups

Number of random effects groups

random_effects_tracker

Object of type RandomEffectsTracker

Value

RandomEffectSamples object

Examples

n <- 100
rfx_group_ids <- sample(1:2, size = n, replace = TRUE)
rfx_basis <- matrix(rep(1.0, n), ncol=1)
num_groups <- length(unique(rfx_group_ids))
num_components <- ncol(rfx_basis)
rfx_tracker <- createRandomEffectsTracker(rfx_group_ids)
rfx_samples <- createRandomEffectSamples(num_components, num_groups, rfx_tracker)