The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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. The methods are described in Hothorn et al. (2006) <doi:10.1198/106186006X133933>, Zeileis et al. (2008) <doi:10.1198/106186008X319331> and Strobl et al. (2007) <doi:10.1186/1471-2105-8-25>.

Version: 1.3-17
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)
LinkingTo: mvtnorm
Suggests: TH.data (≥ 1.0-3), mlbench, colorspace, MASS, vcd, ipred, varImp, randomForest
Published: 2024-08-17
DOI: 10.32614/CRAN.package.party
Author: Torsten Hothorn ORCID iD [aut, cre], Kurt Hornik ORCID iD [aut], Carolin Strobl ORCID iD [aut], Achim Zeileis ORCID iD [aut]
Maintainer: Torsten Hothorn <Torsten.Hothorn at R-project.org>
License: GPL-2
URL: http://party.R-forge.R-project.org
NeedsCompilation: yes
Citation: party citation info
Materials: NEWS
In views: Environmetrics, MachineLearning, Survival
CRAN checks: party results

Documentation:

Reference manual: party.pdf
Vignettes: party with the mob (source, R code)
party: A Laboratory for Recursive Partytioning (source, R code)

Downloads:

Package source: party_1.3-17.tar.gz
Windows binaries: r-devel: party_1.3-17.zip, r-release: party_1.3-17.zip, r-oldrel: party_1.3-17.zip
macOS binaries: r-release (arm64): party_1.3-17.tgz, r-oldrel (arm64): party_1.3-17.tgz, r-release (x86_64): party_1.3-17.tgz, r-oldrel (x86_64): party_1.3-17.tgz
Old sources: party archive

Reverse dependencies:

Reverse depends: moreparty, varImp
Reverse imports: ai, alookr, autoBagging, autostats, aVirtualTwins, CTShiny, CTShiny2, EFS, EpiSemble, GB5mcPred, MachineShop, multilevelPSA, OpEnHiMR, OTrecod, permimp, pheble, PredPsych, PrInDT, PSAboot, psica, rfvimptest, rminer, stablelearner, synthpop, tehtuner, TSDT
Reverse suggests: BiodiversityR, bsnsing, caret, catdata, data.tree, evtree, flowml, fscaret, HSAUR, HSAUR2, htetree, ibawds, iml, ipred, MLInterfaces, mlr, mlrCPO, mlrMBO, ModelMap, partykit, pdp, pec, qeML, rattle, RGraphics, riskRegression, shapr, subsemble, SuperLearner, superMICE
Reverse enhances: vip

Linking:

Please use the canonical form https://CRAN.R-project.org/package=party to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.