# mob_control

##### Control Parameters for Model-based Partitioning

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

models.

- Keywords
- misc

##### 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

*Documentation reproduced from package party, version 1.3-3, License: GPL-2*