party: A Laboratory for Recursive Partytioning

A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available.

Version: 1.0-13
Depends: R (≥ 2.14.0), methods, grid, zoo, sandwich (≥ 1.1-1), strucchange, stats, modeltools (≥ 0.2-21)
Imports: survival, coin
Suggests: TH.data (≥ 1.0-3), mlbench, colorspace, MASS, mvtnorm, vcd
Published: 2014-02-01
Author: Torsten Hothorn [aut, cre], Kurt Hornik [aut], Carolin Strobl [aut], Achim Zeileis [aut]
Maintainer: Torsten Hothorn <Torsten.Hothorn at R-project.org>
License: GPL-2
NeedsCompilation: yes
Citation: party citation info
Materials: NEWS
In views: Environmetrics, MachineLearning, Multivariate, Survival
CRAN checks: party results

Downloads:

Reference manual: party.pdf
Vignettes: party with the mob
party: A Laboratory for Recursive Partytioning
Package source: party_1.0-13.tar.gz
MacOS X binary: party_1.0-13.tgz
Windows binary: party_1.0-13.zip
Old sources: party archive

Reverse dependencies:

Reverse depends: GetR, MAclinical, mobForest, parboost, psychotree
Reverse imports: PSAboot
Reverse suggests: betareg, caret, catdata, evtree, fscaret, HSAUR, HSAUR2, mboost, mlr, ModelGood, multilevelPSA, pec, rattle, RGraphics, SuperLearner