ptrafo

an object of class <code>data.frame</code>.

data

a function to by applied to <code>numeric</code> 
    elements of <code>data</code> returning a matrix with <code>nrow(data)</code>
    rows and an arbitrary number of columns.

numeric_trafo

a function to by applied to <code>factor</code>
    elements of <code>data</code> returning a matrix with <code>nrow(data)</code>
    rows and an arbitrary number of columns (usually a dummy or contrast 
    matrix).

factor_trafo

a function to by applied to 
    elements of class <code>Surv</code> of <code>data</code> returning a 
    matrix with <code>nrow(data)</code> rows and an arbitrary number of columns.

surv_trafo

an optional named list of functions to be applied to the
                   corresponding variables in <code>data</code>.

var_trafo

Transformations of Response or Input Variables

manip

Transformations

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.

Transformations: Function for Data Transformations

Description

Usage

Arguments

Value

Details

Examples