autoboost_gamlss: AutoBoost for GAMLSS (SelectBoost-style)

Description

Runs a c0 grid, picks the c0 that maximizes total confidence, and returns the corresponding sb_gamlss fit.

Usage

autoboost_gamlss(
  formula,
  data,
  family,
  mu_scope,
  sigma_scope = NULL,
  nu_scope = NULL,
  tau_scope = NULL,
  base_sigma = ~1,
  base_nu = ~1,
  base_tau = ~1,
  c0_grid = seq(0.1, 0.9, by = 0.1),
  B = 60,
  sample_fraction = 0.7,
  pi_thr = 0.6,
  k = 2,
  direction = c("both", "forward", "backward"),
  pre_standardize = FALSE,
  trace = TRUE,
  progress = TRUE,
  use_groups = TRUE,
  corr_func = "cor",
  group_fun = SelectBoost::group_func_2,
  ...
)

Value

A SelectBoost_gamlss_grid with summary plots/tables.

Arguments

formula: Base formula for the location \(\mu\) parameter (in the main model call).
data: Data frame.
family: A gamlss.dist family object (e.g., gamlss.dist::NO()).
mu_scope: Formula of candidate terms for \(\mu\).
sigma_scope, nu_scope, tau_scope: Formulas of candidate terms for \(\sigma\), \(\nu\), \(\tau\).
base_sigma, base_nu, base_tau: Optional base (always-included) formulas for \(\sigma\), \(\nu\), \(\tau\).
c0_grid: Numeric vector of c0 values.
B: Number of bootstrap subsamples for stability selection.
sample_fraction: Fraction of rows per subsample (e.g., 0.7).
pi_thr: Selection proportion threshold to define “stable” terms (e.g., 0.6).
k: Penalty weight for stepwise GAIC when engine = "stepGAIC" (default 2).
direction: Stepwise direction for stepGAIC ("both", "forward", "backward").
pre_standardize: Logical; standardize numeric predictors before penalized fits.
trace: Logical; print progress messages.
progress: Logical; show a progress bar in sequential runs.
use_groups: Logical; treat SelectBoost correlation groups during resampling.
corr_func: Correlation function passed to SelectBoost::boost.compcorrs.
group_fun: Grouping function passed to SelectBoost::boost.findgroups.
...: Passed to underlying engines (e.g., to gamlss::gamlss, glmnet, etc.).