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 |
Depends: | randomForest, RColorBrewer |
Imports: | stats, parallel |
Suggests: | gss, knitr, rmarkdown |
Published: | 2017-12-19 |
DOI: | 10.32614/CRAN.package.quantregForest |
Author: | Nicolai Meinshausen |
Maintainer: | Loris Michel <michel at stat.math.ethz.ch> |
BugReports: | http://github.com/lorismichel/quantregForest/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
URL: | http://github.com/lorismichel/quantregForest |
NeedsCompilation: | yes |
In views: | MachineLearning |
CRAN checks: | quantregForest results [issues need fixing before 2024-10-04] |
Reference manual: | quantregForest.pdf |
Package source: | quantregForest_1.3-7.tar.gz |
Windows binaries: | r-devel: quantregForest_1.3-7.zip, r-release: quantregForest_1.3-7.zip, r-oldrel: quantregForest_1.3-7.zip |
macOS binaries: | r-release (arm64): quantregForest_1.3-7.tgz, r-oldrel (arm64): quantregForest_1.3-7.tgz, r-release (x86_64): quantregForest_1.3-7.tgz, r-oldrel (x86_64): quantregForest_1.3-7.tgz |
Old sources: | quantregForest archive |
Reverse imports: | CondIndTests, ConformalSmallest, curvir, geomod |
Reverse suggests: | flowml, fscaret, ModelMap, probably, soilassessment, tidyfit |
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