Smoothed multi-response quantile regression

Usage

smooth_qr(
  x,
  y,
  tau = 0.5,
  degree = 3L,
  intercept = TRUE,
  aheads = 1:n_models,
  ...
)

x: numeric matrix or data.frame of predictors. No intercept should be included.
y: numeric matrix or data.frame of response values
tau: the quantile(s) to be estimated. This is a number (or vector of values) strictly between 0 and 1.
degree: the number of polynomials used for response smoothing. Must be no more than the number of columns in y.
intercept: logical. should the model be estimated with intercept
aheads: Defaults to the vector 1:ncol(y) but if the responses are observed at a different spacing (or appear in a different order), that information should be used here.
...: additional arguments passed on to quantreg::rq. Not all are allowed.

An object of class smoothqr

x <- matrix(rnorm(100 * 10), nrow = 100)
y <- matrix(rnorm(100 * 10), nrow = 100)
out <- smooth_qr(x, y, tau = c(.25, .5, .75))