quantregForest: Quantile Regression Forests (original) (raw)
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 |
| 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:
Downloads:
Reverse dependencies:
| Reverse imports: | CondIndTests, ConformalSmallest, curvir, geomod |
|---|---|
| Reverse suggests: | flowml, marginaleffects, ModelMap, probably, soilassessment, tidyfit, trtf, vetiver |
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