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.


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install.packages("quantregForest")

1.3-6 by Loris Michel, 7 days ago


http://github.com/lorismichel/quantregForest


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


Imported by CondIndTests.

Suggested by GSIF, ModelMap, fscaret.


See at CRAN