## \code{$prefit()} initializes a lslxFitting object. ##
prelslx$set("public",
"prefit",
function(penalty_method = "mcp",
lambda_grid = "default",
delta_grid = "default",
step_grid = "default",
loss = "default",
algorithm = "default",
missing_method = "default",
start_method = "default",
lambda_direction = "default",
lambda_length = 50L,
delta_length = 3L,
threshold_value = 0.3,
subset = NULL,
cv_fold = 1L,
iter_out_max = 100L,
iter_in_max = 50L,
iter_other_max = 500L,
iter_armijo_max = 100L,
tol_out = 1e-3,
tol_in = 1e-3,
tol_other = 1e-7,
step_size = 0.5,
momentum = 0,
armijo = 1e-5,
ridge_cov = 0,
ridge_hessian = 1e-4,
ridge_weight = 1e-4,
warm_start = TRUE,
positive_variance = TRUE,
minimum_variance = 1e-4,
armijo_rule = TRUE,
enforce_cd = TRUE,
random_update = TRUE,
weight_matrix = NULL,
verbose = TRUE) {
control <-
list(
penalty_method = penalty_method,
lambda_grid = lambda_grid,
delta_grid = delta_grid,
step_grid = step_grid,
loss = loss,
algorithm = algorithm,
missing_method = missing_method,
start_method = start_method,
lambda_direction = lambda_direction,
lambda_length = lambda_length,
delta_length = delta_length,
threshold_value = threshold_value,
subset = subset,
cv_fold = cv_fold,
iter_out_max = iter_out_max,
iter_in_max = iter_in_max,
iter_other_max = iter_other_max,
iter_armijo_max = iter_armijo_max,
tol_out = tol_out,
tol_in = tol_in,
tol_other = tol_other,
step_size = step_size,
momentum = momentum,
armijo = armijo,
ridge_cov = ridge_cov,
ridge_hessian = ridge_hessian,
warm_start = warm_start,
positive_variance = positive_variance,
minimum_variance = minimum_variance,
armijo_rule = armijo_rule,
enforce_cd = enforce_cd,
random_update = random_update,
weight_matrix = weight_matrix
)
private$fitting <-
lslxFitting$new(model = private$model,
data = private$data,
control = control)
})
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