samp1.lasso.split: Variabel Screening

In hit: Hierarchical Inference Testing

Description

LASSO function of the HIT algorithem.

Usage

samp1.lasso.split(samp1, x, y, family, alpha, lambda.opt, nfolds,
  penalty.factor, n.samp2, ...)

Arguments

samp1	List of index for subsample (mclapply index).
x	Design matrix, of dimension n x p.
y	Vector of quantitative response variable.
family	Distribution family of y.
alpha	Mixing value for elnet.
lambda.opt	Criterion for optimum selection of cross-validated lasso. Either "lambda.1se" (default) or "lambda.min". See cv.glmnet for more details.
nfolds	Number of folds (default is 10). See
penalty.factor	See glmnet.
n.samp2	Number of individuals in samp2 which is the max. for non zero coefficients.
...	Additional agruments.

hit documentation built on May 2, 2019, 10:15 a.m.