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>.

Install the latest version of this package by entering the following in R:
install.packages("party")
AuthorTorsten Hothorn [aut, cre], Kurt Hornik [aut], Carolin Strobl [aut], Achim Zeileis [aut]
Date of publication2017-04-12 13:53:54 UTC
MaintainerTorsten Hothorn <Torsten.Hothorn@R-project.org>
LicenseGPL-2
Version1.2-3
http://party.R-forge.R-project.org

View on CRAN

Functions

BinaryTree-class Man page
cforest Man page
cforest_classical Man page
cforest_control Man page
cforest_unbiased Man page
coef.mob Man page
conditionalTree Man page
ctree Man page
ctree_control Man page
deviance.mob Man page
edge_simple Man page
ff_trafo Man page
fit-methods Man page
fit,StatModel,LearningSample-method Man page
fitted.mob Man page
ForestControl-class Man page
initialize Man page
initialize,ExpectCovarInfluence-method Man page
initialize,ExpectCovar-method Man page
initialize,LinStatExpectCovar-method Man page
initialize,LinStatExpectCovarMPinv-method Man page
initialize-methods Man page
initialize,svd_mem-method Man page
initialize,VariableFrame-method Man page
initVariableFrame Man page
initVariableFrame,data.frame-method Man page
initVariableFrame,matrix-method Man page
initVariableFrame-methods Man page
LearningSample-class Man page
logLik.mob Man page
mob Man page
mob-class Man page
mob_control Man page
node_barplot Man page
node_bivplot Man page
node_boxplot Man page
node_density Man page
node_hist Man page
node_inner Man page
nodes Man page
nodes,BinaryTree,integer-method Man page
nodes,BinaryTree,numeric-method Man page
node_scatterplot Man page
nodes-methods Man page
node_surv Man page
node_terminal Man page
party_intern Man page
plot.BinaryTree Man page
plot.mob Man page
predict.mob Man page
prettytree Man page
print.mob Man page
proximity Man page
ptrafo Man page
RandomForest-class Man page
readingSkills Man page
residuals.mob Man page
response Man page
response,BinaryTree-method Man page
response-methods Man page
reweight Man page
reweight.glinearModel Man page
reweight.linearModel Man page
sctest.mob Man page
show,BinaryTree-method Man page
show,RandomForest-method Man page
SplittingNode-class Man page
summary.mob Man page
TerminalModelNode-class Man page
TerminalNode-class Man page
TreeControl Man page
TreeControl-class Man page
treeresponse Man page
treeresponse,BinaryTree-method Man page
treeresponse-methods Man page
treeresponse,RandomForest-method Man page
varimp Man page
varimpAUC Man page
weights Man page
weights,BinaryTree-method Man page
weights-methods Man page
weights.mob Man page
weights,RandomForest-method Man page
where Man page
where,BinaryTree-method Man page
where-methods Man page
where,RandomForest-method Man page

Files

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

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.