Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.

Documentation

Manual: quantreg.pdf
Vignette: Quantile Regression

Maintainer: Roger Koenker <rkoenker at illinois.edu>

Author(s): Roger Koenker*, Stephen Portnoy* (Contributions to Censored QR code), Pin Tian Ng* (Contributions to Sparse QR code), Achim Zeileis* (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean* (Contributions to nlrq code), Brian D Ripley* (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)

Install package and any missing dependencies by running this line in your R console:

install.packages("quantreg")


Package quantreg
Materials
URL https://www.r-project.org
Task Views Econometrics , Environmetrics , Optimization , ReproducibleResearch , Robust , SocialSciences , Survival
Version 5.33
Published 2017-04-18
License GPL (>= 2)
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks quantreg check results
Package source quantreg_5.33.tar.gz