samp1.lasso.overall: Variabel Screening

Description Usage Arguments

View source: R/hit.R

Description

LASSO function of the HIT algorithem.

Usage

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samp1.lasso.overall(samp1, x, y, family, alpha, lambda, 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

A vector of lambda values sorted from large to small where the smallest is the optimal value or NULL.

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 30, 2017, 1:27 a.m.