party: mob_control – R documentation

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mob_control

Control Parameters for Model-based Partitioning

Various parameters that control aspects the fitting algorithm for recursively partitioned mob models.

mob_control(alpha = 0.05, bonferroni = TRUE, minsplit = 20, trim = 0.1,
  objfun = deviance, breakties = FALSE, parm = NULL, verbose = FALSE)

`alpha`	numeric significance level. A node is splitted when the (possibly Bonferroni-corrected) p value for any parameter stability test in that node falls below `alpha`.
`bonferroni`	logical. Should p values be Bonferroni corrected?
`minsplit`	integer. The minimum number of observations (sum of the weights) in a node.
`trim`	numeric. This specifies the trimming in the parameter instability test for the numerical variables. If smaller than 1, it is interpreted as the fraction relative to the current node size.
`objfun`	function. A function for extracting the minimized value of the objective function from a fitted model in a node.
`breakties`	logical. Should ties in numeric variables be broken randomly for computing the associated parameter instability test?
`parm`	numeric or character. Number or name of model parameters included in the parameter instability tests (by default all parameters are included).
`verbose`	logical. Should information about the fitting process of `mob` (such as test statistics, p values, selected splitting variables and split points) be printed to the screen?

See mob for more details and references.

A list of class mob_control containing the control parameters.