ColrVS: Optimal subset selection in a Colr-type transformation model

In tramvs: Optimal Subset Selection for Transformation Models

Optimal subset selection in a Colr-type transformation model

Description

Optimal subset selection in a Colr-type transformation model

Usage

ColrVS(
  formula,
  data,
  supp_max = NULL,
  k_max = NULL,
  thresh = NULL,
  init = TRUE,
  m_max = 10,
  parallel = FALSE,
  future_args = list(strategy = "multisession", workers = supp_max),
  ...
)

Arguments

formula	object of class "formula".
data	data frame containing the variables in the model.
supp_max	maximum support which to call abess_tram with.
k_max	maximum splicing size, i.e., number of covariates to swap between active and inactive set, to consider during the splicing algorithm. Defaults to supp.
thresh	threshold when to stop splicing. Defaults to 0.01 * supp * log(p) * log(log(n)) / n, where p denotes the number of predictors and n the sample size.
init	initialize active set. Defaults to TRUE and initializes the active set with those covariates that are most correlated with score residuals of an unconditional modFUN(update(formula, . ~ 1)). If FALSE, the initial active set is drawn at random.
m_max	maximum number of iterating the splicing algorithm.
parallel	toggle for parallel computing via future_lapply
future_args	arguments passed to plan; defaults to a "multisession" with supp_max workers
...	Additional arguments supplied to Colr

Value

See tramvs

tramvs documentation built on Oct. 17, 2026, 5:07 p.m.