Plain SelectBoost Baseline for Functional Predictors — plain

Runs SelectBoost directly on the flattened predictor matrix without the FDA-specific grouping heuristics used by selectboost_fda(). This is useful as a benchmark against the FDA-aware variant.

Usage

plain_selectboost(
  x,
  y = NULL,
  mode = c("fast", "auto"),
  selector = "msgps",
  selector_fun = NULL,
  selector_args = list(),
  groups = NULL,
  family = c("gaussian", "binomial"),
  association = NULL,
  group_method = c("threshold", "community"),
  ...
)

Arguments

x: Any input accepted by as_functional_matrix(), or an fda_design object.
y: Response vector. Leave as NULL when x is an fda_design.
mode: "fast" for a fixed c0 grid or "auto" for the adaptive version.
selector: Base selector used inside SelectBoost. Choose from "msgps", "lasso", "group_lasso", "sparse_group_lasso", the backend-specific aliases "glmnet", "grpreg", "sgl", or provide a custom function.
selector_fun: Optional custom base selector. It must return a coefficient vector of length p.
selector_args: Optional named list of arguments forwarded to the base selector.
groups: Optional feature groups used by grouped base selectors such as "grpreg". Defaults to block-level groups for list inputs.
family: Model family passed to built-in selectors.
association: Optional absolute association matrix used directly by the raw SelectBoost grouping function.
group_method: Functional grouping backend: threshold-based or community-based.
...: Additional arguments passed to SelectBoost::fastboost() or SelectBoost::autoboost().

Value

An object of class plain_selectboost_result.