Control Parameters for Model-based Partitioning

Description

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

Usage

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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