rq.fit.lasso: Quantile Regression w/ Lasso Penalty

In be-green/quantspace: Quantile Regression via Quantile Spacing

Quantile Regression w/ Lasso Penalty

Description

Quantile Regression w/ Lasso Penalty

Usage

rq.fit.lasso(
  X,
  y,
  tau,
  lambda,
  weights,
  scale_x = T,
  method = "two_pass",
  nfold = 10,
  nlambda = 50,
  parallel = F,
  ...
)

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 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

be-green/quantspace documentation built on March 20, 2024, 5:30 p.m.