Create a RandomEffectsModel 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
createRandomEffectsModel(num_components, num_groups)
Arguments
- num_components
Number of "components" or bases defining the random effects regression
- num_groups
Number of random effects groups
Value
RandomEffectsModel 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_model <- createRandomEffectsModel(num_components, num_groups)