R: Control Parameters for Model-based Partitioning

mob_control {party} | R Documentation

## Control Parameters for Model-based Partitioning

### Description

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

### Usage

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

### Arguments

`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?

### Details

See `mob` for more details and references.

### Value

A list of class `mob_control` containing the control parameters.

### See Also

`mob`

[Package party version 1.3-7 Index]