update_beta_sparse_ncv {L2E}

Beta update in L2E sparse regression - NCV

Description

update_beta_sparse_ncv updates beta for L2E sparse regression using existing penalization methods

Usage

update_beta_sparse_ncv(
  y,
  X,
  beta,
  tau,
  lambda,
  penalty,
  max_iter = 100,
  tol = 1e-04
)

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

Value

Returns a list object containing the new estimate for beta (vector) and the number of iterations (scalar) the update step utilized