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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,
  ...
)

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.).

Value

A SelectBoost_gamlss_grid with summary plots/tables.