Control settings for dlmtree model fitting, when used for heterogeneous models

Usage

dlmtree.control.het(
  modifiers = "all",
  modifier.splits = 20,
  modtree.params = c(0.95, 2),
  modtree.step.prob = c(0.25, 0.25, 0.25),
  dlmtree.type = "shared",
  selection.prior = 0.5
)

Arguments

modifiers: string vector containing desired modifiers to be included in a modifier tree. The strings in the vector must match the names of the columns of the data. By default, a modifier tree considers all covariates in the formula as modifiers unless stated otherwise.
modifier.splits: integer value to determine the possible number of splitting points that will be used for a modifier tree.
modtree.params: numerical vector of alpha and beta hyperparameters controlling modifier tree depth. (default: alpha = 0.95, beta = 2)
modtree.step.prob: numerical vector for probability of each step for modifier tree updates: 1) grow, 2) prune, 3) change. (default: c(0.25, 0.25, 0.25))
dlmtree.type: specification of dlmtree type for HDLM: shared (default) or nested.
selection.prior: scalar hyperparameter for sparsity of modifiers. Must be between 0.5 and 1. Smaller value corresponds to increased sparsity of modifiers.

Value

list of control parameters for heterogeneous models.