Package: party
Title: A Laboratory for Recursive Part(y)itioning
Date: $Date: 2006-07-12 22:07:24 +0200 (Wed, 12 Jul 2006) $
Version: 0.8-7
Author: Torsten Hothorn, Kurt Hornik and Achim Zeileis
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
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.
Depends: R (>= 2.0.1), survival, grid, modeltools (>= 0.2-3), coin (>= 0.3-8),
zoo, sandwich (>= 1.1-1), strucchange
Suggests: ipred, mlbench, vcd
LazyLoad: yes
LazyData: yes
License: GPL
Packaged: Mon Jul 17 21:32:57 2006; hothorn

Package: party
Title: A Laboratory for Recursive Part(y)itioning
Date: $Date: 2006-07-12 22:07:24 +0200 (Wed, 12 Jul 2006) $
Version: 0.8-8
Author: Torsten Hothorn, Kurt Hornik and Achim Zeileis
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
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.
Depends: R (>= 2.0.1), survival, grid, modeltools (>= 0.2-3), coin (>= 0.3-8),
zoo, sandwich (>= 1.1-1), strucchange
Suggests: ipred, mlbench, vcd
LazyLoad: yes
LazyData: yes
License: GPL
Packaged: Wed Aug 23 15:34:09 2006; hothorn