quantregForest: Quantile Regression Forests

Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles. It is particularly well suited for high-dimensional data. Predictor variables of mixed classes can be handled. The package is dependent on the package randomForests, written by Andy Liaw.

Version: 1.1
Depends: randomForest
Imports: stats, graphics, grDevices
Suggests: gss
Published: 2015-09-09
Author: Nicolai Meinshausen, Lukas Schiesser
Maintainer: Nicolai Meinshausen <meinshausen at stat.math.ethz.ch>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
In views: MachineLearning
CRAN checks: quantregForest results


Reference manual: quantregForest.pdf
Vignettes: Quantile Regression Forests
Package source: quantregForest_1.1.tar.gz
Windows binaries: r-devel: quantregForest_1.1.zip, r-release: quantregForest_1.1.zip, r-oldrel: quantregForest_1.1.zip
OS X Snow Leopard binaries: r-release: quantregForest_1.1.tgz, r-oldrel: quantregForest_0.2-3.tgz
OS X Mavericks binaries: r-release: quantregForest_1.1.tgz
Old sources: quantregForest archive

Reverse dependencies:

Reverse suggests: fscaret, GSIF, ModelMap