qreg.boot: Bootstraping for Quantile Regression (Asymmetric Laplace...

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

Bootstraping for Quantile Regression (Asymmetric Laplace Regression)

Usage

qreg.boot(
  formula,
  data,
  q = 0.5,
  hd = T,
  parallel = TRUE,
  ncores = 4,
  iter = 1000,
  conf.level = 0.95
)

Arguments

formula	model formula
data	data frame
q	a number corresponding to the quantile of interest (i.e, 0.50 for the median). only one value is allowed in the bootstrap implementation of qreg.
parallel	Whether or not to use parallel processing. Defaults to TRUE.
ncores	Number of cores to use. If not supplied, a cluster on the local machine consisting of the number of system cores minus one is created for the duration of the boot call.
iter	The number of bootstrap replicates. Defaults to 1000.
conf.level	the confidence level for computing the bootstrap confidence intervals. defaults to 0.95.

Value

a quantilereg object containing the contents of a kernelboot object.

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.