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)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.
logical. Should \(p\) values be Bonferroni corrected?
integer. The minimum number of observations (sum of the weights) in a node.
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.
function. A function for extracting the minimized value of the objective function from a fitted model in a node.
logical. Should ties in numeric variables be broken randomly for computing the associated parameter instability test?
numeric or character. Number or name of model parameters included in the parameter instability tests (by default all parameters are included).
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?
A list of class mob_control containing the control parameters.
See mob for more details and references.