mob: MOB is an algorithm for model-based recursive partitioning...

In mirka-henninger/raschTreeEffectSize: Helper functions to use the Mantel-Haenszel effect size measure as a stopping criterion in Rasch trees

Description

MOB is an algorithm for model-based recursive partitioning yielding a tree with fitted models associated with each terminal node. for more details see ?partykit::mob

Usage

mob(
  formula,
  data,
  subset,
  na.action,
  weights,
  offset,
  cluster,
  fit,
  control = mob_control(),
  ...
)

Arguments

formula	symbolic description of the model
data	arguments controlling formula processing via model.frame
subset	arguments controlling formula processing via model.frame
na.action	arguments controlling formula processing via model.frame
weights	optional numeric vector of weights. By default these are treated as case weights but the default can be changed in mob_control
offset	optional numeric vector with an a priori known component to be included in the model y ~ x1 + ... + xk (i.e., only when x variables are specified)
cluster	optional vector (typically numeric or factor) with a cluster ID to be passed on to the fit function and employed for clustered covariances in the parameter stability tests.
fit	function. A function for fitting the model within each node. For details see below.
control	A list with control parameters as returned by mob_control
...	Additional arguments passed to the fit function

mirka-henninger/raschTreeEffectSize documentation built on Nov. 14, 2021, 11:15 p.m.