Learn R Programming

⚠️There's a newer version (1.3-18) of this package.Take me there.

party (version 0.9-1)

A Laboratory for Recursive Part(y)itioning

Description

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. Similar in spirit, the function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) based on parameter instability tests. Furthermore, cforest() provides an implementation of Breiman's random forests based on conditional inference trees. Extensible functionality for visualizing tree-structured regression models is available.

Copy Link

Version

Install

install.packages('party')

Monthly Downloads

16,447

Version

0.9-1

License

GPL

Maintainer

Torsten Hothorn

Last Published

January 29th, 2025

Functions in party (0.9-1)

Initialize Methods

Methods for Function initialize in Package `party'
Control ctree Hyper Parameters

Control for Conditional Inference Trees
mammoexp

Mammography Experience Study
mob_control

Control Parameters for Model-based Partitioning
Panel Generating Functions

Panel-Generators for Visualization of Party Trees
reweight

Re-fitting Models with New Weights
TreeControl Class

Class "TreeControl"
mob

Model-based Recursive Partitioning
LearningSample Class

Class "LearningSample"
SplittingNode Class

Class "SplittingNode"
BinaryTree Class

Class "BinaryTree"
Memory Allocation

Memory Allocation
cforest

Random Forest
Conditional Inference Trees

Conditional Inference Trees
plot.mob

Visualization of MOB Trees
Control Forest Hyper Parameters

Control for Conditional Tree Forests
Transformations

Function for Data Transformations
Fit Methods

Fit `StatModel' Objects to Data
Plot BinaryTree

Visualization of Binary Regression Trees
RandomForest-class

Class "RandomForest"
ForestControl-class

Class "ForestControl"