l2e_regression_sparse_ncv: L2E sparse regression with existing penalization methods

In jocelynchi/L2E-package-demo: Robust Structured Regression via the L2 Criterion

L2E sparse regression with existing penalization methods

Description

l2e_regression_sparse_ncv performs robust sparse regression under the L2 criterion. Available penalties include lasso, MCP and SCAD.

Usage

l2e_regression_sparse_ncv(
  y,
  X,
  beta,
  tau,
  lambda,
  penalty,
  max_iter = 100,
  tol = 1e-04,
  Show.Time = TRUE
)

Arguments

y	Response vector
X	Design matrix
beta	Initial vector of regression coefficients
tau	Initial precision estimate
lambda	Tuning parameter
penalty	Available penalties include lasso, MCP and SCAD.
max_iter	Maximum number of iterations
tol	Relative tolerance
Show.Time	Report the computing time

jocelynchi/L2E-package-demo documentation built on Oct. 6, 2022, 6:05 a.m.