View source: R/update_beta_MM_sparse.R
update_beta_MM_sparse | R Documentation |
update_beta_MM_sparse
updates beta for L2E sparse regression using the distance penalty
update_beta_MM_sparse( y, X, beta, tau, k, rho, stepsize = 0.9, sigma = 0.5, max_iter = 100, tol = 1e-04 )
y |
Response vector |
X |
Design matrix |
beta |
Initial vector of regression coefficients |
tau |
Initial precision estimate |
k |
The number of nonzero entries in the estimated coefficients |
rho |
The parameter in the proximal distance algorithm |
stepsize |
The stepsize parameter for the MM algorithm (0, 1) |
sigma |
The halving parameter sigma (0, 1) |
max_iter |
Maximum number of iterations |
tol |
Relative tolerance |
Returns a list object containing the new estimate for beta (vector) and the number of iterations (scalar) the update step utilized
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.