party: A Laboratory for Recursive Partytioning

The party package (Hothorn, Hornik, and Zeileis 2006) aims at providing a recur-sive part(y)itioning laboratory assembling various high- and low-level tools for building tree-based regression and classification models. This includes conditional inference trees (ctree), conditional inference forests (cforest) and parametric model trees (mob). At 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 infer-ence procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivari-ate response variables and arbitrary measurement scales of the covariates. This vignette comprises a practical guide to exploiting the flexible and extensible computational tools in party for fitting and visualizing conditional inference trees