grpnet  R Documentation 
Solves group elastic net via naive method.
grpnet(
X,
glm,
constraints = NULL,
groups = NULL,
alpha = 1,
penalty = NULL,
offsets = NULL,
lmda_path = NULL,
irls_max_iters = as.integer(10000),
irls_tol = 1e07,
max_iters = as.integer(1e+05),
tol = 1e07,
adev_tol = 0.9,
ddev_tol = 0,
newton_tol = 1e12,
newton_max_iters = 1000,
n_threads = 1,
early_exit = TRUE,
intercept = TRUE,
screen_rule = "pivot",
min_ratio = 0.01,
lmda_path_size = 100,
max_screen_size = NULL,
max_active_size = NULL,
pivot_subset_ratio = 0.1,
pivot_subset_min = 1,
pivot_slack_ratio = 1.25,
check_state = FALSE,
progress_bar = TRUE,
warm_start = NULL
)
X 
Feature matrix. 
glm 
GLM object. 
constraints 
Constraints. 
groups 
Groups. 
alpha 
Elastic net parameter. 
penalty 
Penalty factor. 
offsets 
Offsets. 
lmda_path 
The regularization path. 
irls_max_iters 
Maximum number of IRLS iterations. 
irls_tol 
IRLS convergence tolerance. 
max_iters 
Maximum number of coordinate descents. 
tol 
Coordinate descent convergence tolerance. 
adev_tol 
Percent deviance explained tolerance. 
ddev_tol 
Difference in percent deviance explained tolerance. 
newton_tol 
Convergence tolerance for the BCD update. 
newton_max_iters 
Maximum number of iterations for the BCD update. 
n_threads 
Number of threads. 
early_exit 

intercept 

screen_rule 
Screen rule. 
min_ratio 
Ratio between largest and smallest regularization. 
lmda_path_size 
Number of regularizations. 
max_screen_size 
Maximum number of screen groups. 
max_active_size 
Maximum number of active groups. 
pivot_subset_ratio 
Subset ratio of pivot rule. 
pivot_subset_min 
Minimum subset of pivot rule. 
pivot_slack_ratio 
Slack ratio of pivot rule. 
check_state 
Check state. 
progress_bar 
Progress bar. 
warm_start 
Warm start. 
State of the solver.
set.seed(0)
n < 100
p < 200
X < matrix(rnorm(n * p), n, p)
y < X[,1] * rnorm(1) + rnorm(n)
state < grpnet(X, glm.gaussian(y))
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