lqr: Robust Linear Quantile Regression

It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.

Version: 5.0
Imports: graphics, stats, spatstat.geom, numDeriv, MomTrunc, quantreg, MASS
Suggests: ald
Published: 2022-08-15
Author: Christian E. Galarza, Luis Benites, Marcelo Bourguignon, Victor H. Lachos
Maintainer: Christian E. Galarza <cgalarza88 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: lqr results

Documentation:

Reference manual: lqr.pdf

Downloads:

Package source: lqr_5.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: lqr_5.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Old sources: lqr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=lqr to link to this page.