Marginal pre-screening algorithm given lasso output

Given the estimated lasso coefficients, return the indices of the first num_to_keep variables that enter the model

Usage

prescreen_lasso(beta_hat_lasso, num_to_keep)

Arguments

beta_hat_lasso

(p x L) matrix of estimated coefficients from the lasso; sparsity decreases in the column index L

num_to_keep

number of variables to return in the screening process

Value

ind_keep: the indices of the variables to keep