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. The methods are described in Hothorn et al. (2006) , Zeileis et al. (2008) and Strobl et al. (2007) .

Maintainer: Torsten Hothorn <Torsten.Hothorn at R-project.org>

Author(s): Torsten Hothorn*, Kurt Hornik*, Carolin Strobl*, Achim Zeileis*

Install package and any missing dependencies by running this line in your R console:

install.packages("party")

Depends R (>= 3.0.0), methods, grid, stats, mvtnorm(>=1.0-2), modeltools(>=0.2-21), strucchange
Imports survival(>=2.37-7), coin(>=1.1-0), zoo, sandwich(>=1.1-1)
Suggests TH.data(>=1.0-3), mlbench, colorspace, MASS, vcd, ipred
Enhances
Linking to mvtnorm

Package party
Materials
URL http://party.R-forge.R-project.org
Task Views Environmetrics , MachineLearning , Multivariate , Survival
Version 1.2-3
Published 2017-04-12
License GPL-2
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks party check results
Package source party_1.2-3.tar.gz