LASSO function of the HIT algorithem.
1 2 | samp1.lasso.overall(samp1, x, y, family, alpha, lambda, penalty.factor, n.samp2,
...)
|
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 |
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. |
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