rq.fit.lasso.Rd
Quantile Regression w/ Lasso Penalty
rq.fit.lasso( X, y, tau, lambda, weights, scale_x = T, method = "agd", nfold = 10, nlambda = 50, parallel = F, ... )
X | Design matrix, X |
---|---|
y | outcome variable, y |
tau | quantile to estimate |
lambda | penalty parameter |
weights | optional vector of weights |
scale_x | whether to scale the design matrix before estimation |
method | method to use when fitting underlying quantile regression algorithm |
nfold | number of folds to use when cross-validating |
nlambda | number of lambdas to search over. |
parallel | whether to run cv search in parallel, if applicable |
... | other arguments to pass to underlying fitting algorithm |