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 'randomForest', written by Andy Liaw.

Version:	1.3-7.1
Depends:	randomForest, RColorBrewer
Imports:	stats, parallel
Suggests:	gss, knitr, rmarkdown
Published:	2024-10-07
DOI:	10.32614/CRAN.package.quantregForest
Author:	Nicolai Meinshausen [aut], Loris Michel [cre]
Maintainer:	Loris Michel <michel at stat.math.ethz.ch>
BugReports:	https://github.com/lorismichel/quantregForest/issues
License:	GPL-2 | GPL-3 [expanded from: GPL]
URL:	https://github.com/lorismichel/quantregForest
NeedsCompilation:	yes
In views:	MachineLearning
CRAN checks:	quantregForest results

Documentation:

Reference manual:

quantregForest.pdf

Downloads:

Package source:	quantregForest_1.3-7.1.tar.gz
Windows binaries:	r-devel: quantregForest_1.3-7.1.zip, r-release: quantregForest_1.3-7.1.zip, r-oldrel: quantregForest_1.3-7.1.zip
macOS binaries:	r-release (arm64): quantregForest_1.3-7.1.tgz, r-oldrel (arm64): quantregForest_1.3-7.1.tgz, r-release (x86_64): quantregForest_1.3-7.1.tgz, r-oldrel (x86_64): quantregForest_1.3-7.1.tgz
Old sources:	quantregForest archive

Reverse dependencies:

Reverse imports:	CondIndTests, ConformalSmallest, curvir, geomod
Reverse suggests:	flowml, fscaret, ModelMap, probably, soilassessment, tidyfit

Linking:

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