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.


Reference manual

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1.3-7 by Loris Michel, 3 years ago


Report a bug at http://github.com/lorismichel/quantregForest/issues

Browse source code at https://github.com/cran/quantregForest

Authors: Nicolai Meinshausen

Documentation:   PDF Manual  

Task views: Machine Learning & Statistical Learning

GPL license

Imports stats, parallel

Depends on randomForest, RColorBrewer

Suggests gss, knitr, rmarkdown

Imported by CondIndTests, ParallelDSM, soilassessment.

Suggested by ModelMap, fscaret.

See at CRAN