abess_mmlt: Optimal subset selection for multivariate transformation...

In tramvs: Optimal Subset Selection for Transformation Models

Optimal subset selection for multivariate transformation models

Description

Optimal subset selection for multivariate transformation models

Usage

abess_mmlt(
  mltargs,
  supp,
  k_max = supp,
  thresh = NULL,
  init = TRUE,
  m_max = 10,
  m0 = NULL,
  ...
)

Arguments

mltargs	Arguments passed to mmlt
supp	support size of the coefficient vector
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.
m0	Transformation model for initialization
...	Currently ignored

Value

List containing the fitted model via mmlt, active set A and inactive set I.

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