Beta update in L2E trend filtering regression using Lasso

update_beta_TF_lasso updates beta in L2E trend filtering regression using the Lasso penalty

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

Arguments

y

Response vector
X

Design matrix
beta

Initial vector of regression coefficients
tau

Initial precision estimate
D

The fusion matrix
lambda

The tuning parameter
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