selected_variables: Bolasso-selected Variables

In bolasso: Model Consistent Lasso Estimation Through the Bootstrap

Bolasso-selected Variables

Description

Identifies covariates that are selected by the Bolasso algorithm at the user-defined threshold. There are two variable selection criterion to choose between; Variable Inclusion Probability ("vip") introduced in the original Bolasso paper (Bach, 2008) and further developed by Bunea et al. (2011), and the Quantile ("qnt") approach proposed by Abram et al. (2016). The desired threshold value is 1 - alpha, where alpha is some (typically small) significance level.

Usage

selected_variables(
  object,
  threshold = 0.95,
  method = c("vip", "qnt"),
  var_names_only = FALSE,
  ...
)

Arguments

object	An object of class bolasso.
threshold	A numeric between 0 and 1, specifying the variable selection threshold to use.
method	The variable selection method to use. The two valid options are c("vip", "qnt"). The default "vip" and is the method described in the original Bach (2008) and complementary Bunea et al. (2011) works. The "qnt" method is the method proposed by Abram et al. (2016).
var_names_only	A boolean value. When var_names_only = FALSE (the default value) this function will return a tibble::tibble of selected covariates and their corresponding coefficients across all bootstrap replicates. When var_names_only == TRUE, it will return a vector containing all selected covariate names.
...	Additional arguments to pass to coef on objects with class bolasso or bolass_fast.

Details

This function returns either a tibble::tibble of selected covariates and their corresponding coefficients across all bootstrap replicates, or a vector of selected covariate names.

Value

A tibble with each selected variable and its respective coefficient for each bootstrap replicate OR a vector of the names of all selected variables. In the case of a multinomial regression this will return a list with one element for each unique outcome. Each element will then be either a tibble of coefficients or a list of names.

See Also

glmnet::coef.glmnet() and gamlr:::coef.gamlr for details on additional arguments to pass to ....

bolasso documentation built on March 19, 2026, 5:08 p.m.