rq.fit.sfn_start_val: Sparse Regression Quantile Fitting with Weights

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

Sparse Regression Quantile Fitting with Weights

Description

Sparse Regression Quantile Fitting with Weights

Usage

rq.fit.sfn_start_val(
  X,
  y,
  tau = 0.5,
  rhs = (1 - tau) * c(t(a) %*% rep(1, length(y))),
  control,
  sv,
  weights = NULL,
  lambda,
  ...
)

Arguments

X	structure of the design matrix X stored in csr format
y	outcome vector
tau	desired quantile
rhs	the right-hand-side of the dual problem; regular users shouldn't need to specify this, but in special cases can be quite usefully altered to meet special needs. See e.g. Section 6.8 of Koenker (2005).
control	control parameters for fitting routines: see quantreg::sfn.control()
sv	starting value for optimization, useful when bootstrapping
weights	Optional vector of weights for regression
lambda	ignored
...	other parameters, ignored

Details

A wrapper around the rq.fit.sfn function from the quantreg package, extended to allow for a user-supplied starting value and weights

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