Description Usage Arguments Value
Fitting A sparse Total Least Square model Using PALM algorithm
1 2 3 |
X |
The observation data matrix |
y |
The observation response vector |
center |
Y = Y - mean(Y) and X = X - mean(X) |
lambda |
The regularized lambda vector |
nlambda |
The Number of lambda |
lmin_ratio |
lambda_max / lambda_min |
alpha |
alpha parameter for elastic net penalty (0,1](Ridge Regression –> Lasso) |
eps_abs |
Absolutely epsilon for generated varaince vector |
eps_rel |
Relative epsilon for objective function value of generated vector |
maxit |
The maximal iteration of PALM algorithm |
warm_start |
Warm start for regularizer parameter tuning |
STLS_fit
object
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.