party: A Laboratory for Recursive Partytioning

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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.

Author
Torsten Hothorn [aut, cre], Kurt Hornik [aut], Carolin Strobl [aut], Achim Zeileis [aut]
Date of publication
2016-11-28 13:04:40
Maintainer
Torsten Hothorn <Torsten.Hothorn@R-project.org>
License
GPL-2
Version
1.1-2
URLs

View on CRAN

Man pages

BinaryTree-class
Class "BinaryTree"
cforest
Random Forest
cforest_control
Control for Conditional Tree Forests
ctree
Conditional Inference Trees
ctree_control
Control for Conditional Inference Trees
fit-methods
Fit 'StatModel' Objects to Data
ForestControl-class
Class "ForestControl"
initialize-methods
Methods for Function initialize in Package 'party'
initVariableFrame-methods
Set-up VariableFrame objects
LearningSample-class
Class "LearningSample"
mob
Model-based Recursive Partitioning
mob_control
Control Parameters for Model-based Partitioning
panelfunctions
Panel-Generators for Visualization of Party Trees
party_intern
Call internal functions.
plot.BinaryTree
Visualization of Binary Regression Trees
plot.mob
Visualization of MOB Trees
prettytree
Print a tree.
RandomForest-class
Class "RandomForest"
readingSkills
Reading Skills
reweight
Re-fitting Models with New Weights
SplittingNode-class
Class "SplittingNode"
Transformations
Function for Data Transformations
TreeControl-class
Class "TreeControl"
varimp
Variable Importance

Files in this package

party
party/inst
party/inst/CITATION
party/inst/NEWS
party/inst/doc
party/inst/doc/party.pdf
party/inst/doc/party.Rnw
party/inst/doc/MOB.R
party/inst/doc/MOB.pdf
party/inst/doc/party.R
party/inst/doc/MOB.Rnw
party/inst/doxygen.cfg
party/tests
party/tests/RandomForest-regtest.Rout.save
party/tests/Utils-regtest.R
party/tests/mob.R
party/tests/Examples
party/tests/Examples/party-Ex.Rout.save
party/tests/LinearStatistic-regtest.Rout.save
party/tests/Distributions.Rout.save
party/tests/Distributions.R
party/tests/mob.Rout.save
party/tests/TestStatistic-regtest.R
party/tests/TestStatistic-regtest.Rout.save
party/tests/bugfixes.Rout.save
party/tests/Utils-regtest.Rout.save
party/tests/Predict-regtest.R
party/tests/RandomForest-regtest.R
party/tests/TreeGrow-regtest.R
party/tests/t1.RData
party/tests/LinearStatistic-regtest.R
party/tests/TreeGrow-regtest.Rout.save
party/tests/bugfixes.R
party/tests/Predict-regtest.Rout.save
party/src
party/src/Predict.c
party/src/Makevars
party/src/IndependenceTest.h
party/src/RandomForest.c
party/src/Utils.h
party/src/Classes.c
party/src/Convenience.h
party/src/SurrogateSplits.c
party/src/Distributions.h
party/src/S3Classes.h
party/src/Classes.h
party/src/Memory.c
party/src/party.h
party/src/Convenience.c
party/src/IndependenceTest.c
party/src/SurrogateSplits.h
party/src/LinearStatistic.h
party/src/TestStatistic.h
party/src/LinearStatistic.c
party/src/Predict.h
party/src/Utils.c
party/src/Memory.h
party/src/TreeGrow.h
party/src/Splits.c
party/src/TestStatistic.c
party/src/TreeGrow.c
party/src/Node.h
party/src/Splits.h
party/src/Node.c
party/src/Distributions.c
party/src/S3Classes.c
party/NAMESPACE
party/demo
party/demo/strucchange-perm.R
party/demo/00Index
party/data
party/data/readingSkills.rda
party/R
party/R/Utils.R
party/R/zInitMethods.R
party/R/varimp.R
party/R/ConditionalTree.R
party/R/Print.R
party/R/internals.R
party/R/Plot.R
party/R/MOB-Plot.R
party/R/MOB-Utils.R
party/R/reweight.R
party/R/Predict.R
party/R/Variables.R
party/R/MOB.R
party/R/RandomForest.R
party/R/AAA.R
party/R/Classes.R
party/vignettes
party/vignettes/MOB.Rout.save
party/vignettes/partyrefs.bib
party/vignettes/party.Rnw
party/vignettes/party.Rout.save
party/vignettes/MOB.Rnw
party/MD5
party/build
party/build/vignette.rds
party/DESCRIPTION
party/man
party/man/panelfunctions.Rd
party/man/mob_control.Rd
party/man/prettytree.Rd
party/man/RandomForest-class.Rd
party/man/SplittingNode-class.Rd
party/man/cforest_control.Rd
party/man/LearningSample-class.Rd
party/man/plot.BinaryTree.Rd
party/man/initialize-methods.Rd
party/man/plot.mob.Rd
party/man/ctree_control.Rd
party/man/mob.Rd
party/man/party_intern.Rd
party/man/readingSkills.Rd
party/man/Transformations.Rd
party/man/fit-methods.Rd
party/man/cforest.Rd
party/man/TreeControl-class.Rd
party/man/varimp.Rd
party/man/BinaryTree-class.Rd
party/man/ctree.Rd
party/man/ForestControl-class.Rd
party/man/initVariableFrame-methods.Rd
party/man/reweight.Rd
party/cleanup