Quantile Regression w/ Lasso Penalty

Quantile Regression w/ Lasso Penalty

rq.fit.post_lasso(
  X,
  y,
  tau,
  lambda,
  weights,
  scale_x = T,
  method = "agd",
  nfold = 5,
  nlambda = 10,
  ...
)

Arguments

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 argument to be passed to quantreg::rq

nfold

number of folds to use when cross-validating

nlambda

number of lambdas to search over when cross-validating

...

other arguments to pass to underlying fitting algorithm